A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.
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.
Type
Journal articleSubject
FemaleHost-Pathogen Interactions
Humans
Influenza A Virus, H1N1 Subtype
Influenza A Virus, H3N2 Subtype
Influenza, Human
Male
Middle Aged
Oligonucleotide Array Sequence Analysis
Reverse Transcriptase Polymerase Chain Reaction
Species Specificity
Time Factors
Transcriptome
Young Adult
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https://hdl.handle.net/10161/8944Published Version (Please cite this version)
10.1371/journal.pone.0052198Publication Info
Woods, Christopher W; McClain, Micah T; Chen, Minhua; Zaas, Aimee K; Nicholson, Bradly
P; Varkey, Jay; ... Ginsburg, Geoffrey S (2013). A host transcriptional signature for presymptomatic detection of infection in humans
exposed to influenza H1N1 or H3N2. PLoS One, 8(1). pp. e52198. 10.1371/journal.pone.0052198. Retrieved from https://hdl.handle.net/10161/8944.This is constructed from limited available data and may be imprecise. To cite this
article, please review & use the official citation provided by the journal.
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Show full item recordScholars@Duke
Lawrence Carin
Professor of Electrical and Computer Engineering
Lawrence Carin earned the BS, MS, and PhD degrees in electrical engineering at the
University of Maryland, College Park, in 1985, 1986, and 1989, respectively. In 1989
he joined the Electrical Engineering Department at Polytechnic University (Brooklyn)
as an Assistant Professor, and became an Associate Professor there in 1994. In September
1995 he joined the Electrical and Computer Engineering (ECE) Department at Duke University,
where he is now a Professor. He was ECE Department Chair from 2011
Geoffrey Steven Ginsburg
Adjunct Professor in the Department of Medicine
Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms
for developing and translating genomic information into medical practice and the integration
of personalized medicine into health care.
Joseph E. Lucas
Associate Research Professor in the Social Science Research Institute
This author no longer has a Scholars@Duke profile, so the information shown here reflects
their Duke status at the time this item was deposited.
Micah Thomas McClain
Associate Professor of Medicine
Elizabeth Anne Ramsburg
Adjunct Assistant Professor in the Department of Molecular Genetics and Microbiology
In principle, most viral infections can be prevented by effective and timely vaccination.
In the past several decades however, the rapid emergence and spread into new geographical
areas of viruses such as dengue, West Nile virus, HIV, and the highly pathogenic avian
influenzas has outpaced the development of preventative vaccines. The major focus
of research in the Ramsburg lab is to develop novel vaccines based on recombinant
viruses for the prevention of viral diseases, and to better char
This author no longer has a Scholars@Duke profile, so the information shown here reflects
their Duke status at the time this item was deposited.
Christopher Wildrick Woods
Professor of Medicine
1. Emerging Infections 2. Global Health 3. Epidemiology of infectious diseases
4. Clinical microbiology and diagnostics 5. Bioterrorism Preparedness 6. Surveillance
for communicable diseases 7. Antimicrobial resistance
Aimee Kirsch Zaas
Professor of Medicine
Medical education Genomic applications for diagnosis of infectious diseases Genomic
applications for prediction of infectious diseases
Alphabetical list of authors with Scholars@Duke profiles.

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