Host gene expression classifiers diagnose acute respiratory illness etiology.

Tsalik, Ephraim L

Henao, Ricardo

Nichols, Marshall

Burke, Thomas

Ko, Emily R

McClain, Micah T

Hudson, Lori L

Mazur, Anna

Freeman, Debra H

Veldman, Tim

Langley, Raymond J

Quackenbush, Eugenia B

Glickman, Seth W

Cairns, Charles B

Jaehne, Anja K

Rivers, Emanuel P

Otero, Ronny M

Zaas, Aimee K

Kingsmore, Stephen F

Lucas, Joseph

Fowler, Vance G

Carin, Lawrence

Ginsburg, Geoffrey S

Woods, Christopher W

United States

2016-08-01T14:22:45Z

2016-01-20

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.

http://www.ncbi.nlm.nih.gov/pubmed/26791949

8/322/322ra11

1946-6242

https://hdl.handle.net/10161/12536

eng

American Association for the Advancement of Science (AAAS)

Sci Transl Med

10.1126/scitranslmed.aad6873

Adolescent

Adult

Aged

Aged, 80 and over

Case-Control Studies

Child

Child, Preschool

Cohort Studies

Coinfection

Demography

Female

Gene Expression Regulation

Host-Pathogen Interactions

Humans

Male

Middle Aged

Reproducibility of Results

Respiratory Tract Infections

Signal Transduction

Young Adult

Host gene expression classifiers diagnose acute respiratory illness etiology.

Journal article

Tsalik, Ephraim L|0000-0002-6417-2042

Henao, Ricardo|0000-0003-4980-845X

Burke, Thomas|0000-0003-0592-5822

Fowler, Vance G|0000-0002-8048-0897

Ginsburg, Geoffrey S|0000-0003-4739-9808

Woods, Christopher W|0000-0001-7240-2453

http://www.ncbi.nlm.nih.gov/pubmed/26791949

322ra11

322

Basic Science Departments

Biomedical Engineering

Biostatistics & Bioinformatics

Clinical Science Departments

Duke

Duke Cancer Institute

Duke Clinical Research Institute

Electrical and Computer Engineering

Global Health Institute

Institutes and Centers

Institutes and Provost's Academic Units

Medicine

Medicine, Cardiology

Medicine, Hospitalists

Medicine, Infectious Diseases

Molecular Genetics and Microbiology

Pathology

Pratt School of Engineering

School of Medicine

School of Nursing

School of Nursing - Secondary Group

Social Science Research Institute

University Institutes and Centers

Published

8