Research ArticleInfectious Disease

Host gene expression classifiers diagnose acute respiratory illness etiology

Science Translational Medicine  20 Jan 2016:
Vol. 8, Issue 322, pp. 322ra11
DOI: 10.1126/scitranslmed.aad6873

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Resisting antibiotics

No matter the cause, acute respiratory infections can be miserable. Indeed, these infections are one of the most common reasons for seeking medical care. A clear diagnostic can help medical practitioners resist the patient-induced pressure to prescribe antibiotics as a catch-all therapy, which increases the risk of bacteria developing antibiotic resistance. Now, Tsalik et al. report clear differences in host gene expression induced by bacterial and viral infection as well as by noninfectious illness. These differences can be used to discriminate between these groups, and a host gene expression classifier may be a helpful diagnostic platform to curb unnecessary antibiotic use.

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.

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