A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.
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 in...
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doaj-dfa93b3d53ac4136ac04375cfd974d782020-11-25T02:34:22ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0181e5219810.1371/journal.pone.0052198A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.Christopher W WoodsMicah T McClainMinhua ChenAimee K ZaasBradly P NicholsonJay VarkeyTimothy VeldmanStephen F KingsmoreStephen F KingsmoreYongsheng HuangRobert Lambkin-WilliamsAnthony G GilbertAlfred O HeroElizabeth RamsburgSeth GlickmanJoseph E LucasLawrence CarinGeoffrey S GinsburgThere 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.http://europepmc.org/articles/PMC3541408?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Christopher W Woods Micah T McClain Minhua Chen Aimee K Zaas Bradly P Nicholson Jay Varkey Timothy Veldman Stephen F Kingsmore 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 |
spellingShingle |
Christopher W Woods Micah T McClain Minhua Chen Aimee K Zaas Bradly P Nicholson Jay Varkey Timothy Veldman Stephen F Kingsmore 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 A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2. PLoS ONE |
author_facet |
Christopher W Woods Micah T McClain Minhua Chen Aimee K Zaas Bradly P Nicholson Jay Varkey Timothy Veldman Stephen F Kingsmore 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 |
author_sort |
Christopher W Woods |
title |
A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2. |
title_short |
A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2. |
title_full |
A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2. |
title_fullStr |
A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2. |
title_full_unstemmed |
A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2. |
title_sort |
host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza h1n1 or h3n2. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2013-01-01 |
description |
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. |
url |
http://europepmc.org/articles/PMC3541408?pdf=render |
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