martes, 22 de enero de 2013

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

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

Research Article

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

  • Christopher W. Woods equal contributor mail,
    equal contributor Contributed equally to this work with: Christopher W. Woods, Micah T. McClain
    chris.woods@duke.edu (CW); geoffrey.ginsburg@duke.edu (GG)
    Affiliations: Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, United States of America, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, United States of America, Durham Veteran’s Affairs Medical Center, Durham, North Carolina, United States of America
    X
  • Micah T. McClain equal contributor,
    equal contributor Contributed equally to this work with: Christopher W. Woods, Micah T. McClain
    Affiliations: Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, United States of America, Durham Veteran’s Affairs Medical Center, Durham, North Carolina, United States of America
    X
  • Minhua Chen,
    Affiliation: Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina, United States of America
    X
  • Aimee K. Zaas,
    Affiliations: Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, United States of America, Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, United States of America
    X
  • Bradly P. Nicholson,
    Affiliation: Durham Veteran’s Affairs Medical Center, Durham, North Carolina, United States of America
    X
  • Jay Varkey,
    Affiliation: Division of Infectious Diseases, Duke University Medical Center, Durham, North Carolina, United States of America
    X
  • Timothy Veldman,
    Affiliation: Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, United States of America
    X
  • Stephen F. Kingsmore,
    Affiliation: National Center for Genome Resources, Santa Fe, New Mexico, United States of America
    X
  • Yongsheng Huang,
    Affiliation: Center for Computational Biology and Bioinformatics, University of Michigan, Ann Arobor, Michigan, United States of America
    X
  • Robert Lambkin-Williams,
    Affiliation: Retroscreen Virology, London, United Kingdom
    X
  • Anthony G. Gilbert,
    Affiliation: Retroscreen Virology, London, United Kingdom
    X
  • Alfred O. Hero III,
    Affiliation: Center for Computational Biology and Bioinformatics, University of Michigan, Ann Arobor, Michigan, United States of America
    X
  • Elizabeth Ramsburg,
    Affiliation: Duke Human Vaccine Institute, Duke University Medical Center, Durham, North Carolina, United States of America
    X
  •  [ ... ],
  • Seth Glickman,
    Affiliation: Department of Emergency Medicine, University of North Carolina-Chapel-Hill, Chapel Hill, North Carolina, United States of America
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  • Joseph E. Lucas,
    Affiliation: Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, United States of America
    X
  • Lawrence Carin,
    Affiliation: Department of Electrical and Computer Engineering, Duke University, Durham, North Carolina, United States of America
    X
  • Geoffrey S. Ginsburg mail
    chris.woods@duke.edu (CW); geoffrey.ginsburg@duke.edu (GG)
    Affiliation: Institute for Genome Sciences and Policy, Duke University Medical Center, Durham, North Carolina, United States of America
    X
  • , [ view all ]
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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.

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