A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.
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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.
Influenza A Virus, H1N1 Subtype
Influenza A Virus, H3N2 Subtype
Oligonucleotide Array Sequence Analysis
Reverse Transcriptase Polymerase Chain Reaction
Published Version (Please cite this version)10.1371/journal.pone.0052198
Publication InfoCarin, Lawrence; Chen, M; Gilbert, AG; Ginsburg, Geoffrey Steven; Glickman, Seth W; Hero, Alfred; ... Zaas, Aimee Kirsch (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 http://hdl.handle.net/10161/8944.
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James L. Meriam 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 Engineering Department at Duke University, where he is now a Professor, and Vice Provost for Research. From 2003-2014 he held th
Professor 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.
Associate Research Professor in the Social Science Research Institute
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
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
Associate Professor of Medicine
Medical education Genomic applications for diagnosis of infectious diseases Genomic applications for prediction of infectious diseases
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