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Sci Transl Med. 2016 Jan 20;8(322):322ra11. doi: 10.1126/scitranslmed.aad6873.

Host gene expression classifiers diagnose acute respiratory illness etiology.

Author information

  • 1Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708, USA. Emergency Medicine Service, Durham Veteran's Affairs Medical Center, Durham, NC 27705, USA. Division of Infectious Diseases and International Health, Department of Medicine, Duke University, Durham, NC 27710, USA.
  • 2Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708, USA. Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA.
  • 3Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708, USA.
  • 4Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708, USA. Duke Regional Hospital, Department of Medicine, Duke University, Durham, NC 27710, USA.
  • 5Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708, USA. Division of Infectious Diseases and International Health, Department of Medicine, Duke University, Durham, NC 27710, USA. Section for Infectious Diseases, Medicine Service, Durham Veteran's Affairs Medical Center, Durham, NC 27705, USA.
  • 6Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708, USA. Division of Infectious Diseases and International Health, Department of Medicine, Duke University, Durham, NC 27710, USA.
  • 7Immunology Division, Lovelace Respiratory Research Institute, Albuquerque, NM 87108, USA.
  • 8Department of Emergency Medicine, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA.
  • 9Department of Emergency Medicine, University of North Carolina School of Medicine, Chapel Hill, NC 27599, USA. Department of Emergency Medicine, University of Arizona Health Sciences Center, Tucson, AZ 85724, USA.
  • 10Department of Emergency Medicine, Henry Ford Hospital, Wayne State University, Detroit, MI 48202, USA.
  • 11Rady Pediatric Genomic and Systems Medicine Institute, Rady Children's Hospital, San Diego, CA 92123, USA.
  • 12Division of Infectious Diseases and International Health, Department of Medicine, Duke University, Durham, NC 27710, USA.
  • 13Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708, USA. geoffrey.ginsburg@duke.edu chris.woods@duke.edu.
  • 14Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC 27708, USA. Division of Infectious Diseases and International Health, Department of Medicine, Duke University, Durham, NC 27710, USA. Section for Infectious Diseases, Medicine Service, Durham Veteran's Affairs Medical Center, Durham, NC 27705, USA. geoffrey.ginsburg@duke.edu chris.woods@duke.edu.

Abstract

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.

PMID:
26791949
PMCID:
PMC4905578
[Available on 2017-01-20]
DOI:
10.1126/scitranslmed.aad6873
[PubMed - indexed for MEDLINE]
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