Host gene expression classifiers diagnose acute respiratory illness etiology.
Repository Usage Stats
Acute respiratory infections caused by bacterial or viral pathogens are among the most common reasons for seeking medical care. Despite improvements in pathogen-based diagnostics, most patients receive inappropriate antibiotics. Host response biomarkers offer an alternative diagnostic approach to direct antimicrobial use. This observational cohort study determined whether host gene expression patterns discriminate noninfectious from infectious illness and bacterial from viral causes of acute respiratory infection in the acute care setting. Peripheral whole blood gene expression from 273 subjects with community-onset acute respiratory infection (ARI) or noninfectious illness, as well as 44 healthy controls, was measured using microarrays. Sparse logistic regression was used to develop classifiers for bacterial ARI (71 probes), viral ARI (33 probes), or a noninfectious cause of illness (26 probes). Overall accuracy was 87% (238 of 273 concordant with clinical adjudication), which was more accurate than procalcitonin (78%, P < 0.03) and three published classifiers of bacterial versus viral infection (78 to 83%). The classifiers developed here externally validated in five publicly available data sets (AUC, 0.90 to 0.99). A sixth publicly available data set included 25 patients with co-identification of bacterial and viral pathogens. Applying the ARI classifiers defined four distinct groups: a host response to bacterial ARI, viral ARI, coinfection, and neither a bacterial nor a viral response. These findings create an opportunity to develop and use host gene expression classifiers as diagnostic platforms to combat inappropriate antibiotic use and emerging antibiotic resistance.
Aged, 80 and over
Gene Expression Regulation
Reproducibility of Results
Respiratory Tract Infections
Published Version (Please cite this version)10.1126/scitranslmed.aad6873
Publication InfoTsalik, Ephraim L; Henao, Ricardo; Nichols, Marshall; Burke, Thomas; Ko, Emily R; McClain, Micah T; ... Woods, Christopher W (2016). Host gene expression classifiers diagnose acute respiratory illness etiology. Sci Transl Med, 8(322). pp. 322ra11. 10.1126/scitranslmed.aad6873. Retrieved from https://hdl.handle.net/10161/12536.
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.
More InfoShow full item record
Manager, Systems Project
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
Vance Garrison Fowler Jr.
Florence McAlister Distinguished Professor of Medicine
Determinants of Outcome in Patients with Staphylococcus aureus Bacteremia Antibacterial ResistancePathogenesis of Bacterial Infections Tropical medicine/International Health
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.
Associate Professor in Biostatistics & Bioinformatics
Emily Ray Ko
Assistant Professor of Medicine
Clinical and translational research, COVID-19 therapeutics, clinical biomarkers for infectious disease.
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
Adjunct Associate Professor in the Department of Medicine
My research at Duke has focused on understanding the dynamic between host and pathogen so as to discover and develop host-response markers that can diagnose and predict health and disease. This new and evolving approach to diagnosing illness has the potential to significantly impact individual as well as public health considering the rise of antibiotic resistance. With any potential infectious disease diagnosis, it is difficult, if not impossible, to determine at the time of pre
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.
Articles written by Duke faculty are made available through the campus open access policy. For more information see: Duke Open Access Policy
Rights for Collection: Scholarly Articles
Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info