Journal article
Gene Expression-Based Classifiers Identify Staphylococcus aureus Infection in Mice and Humans
PloS one, v 8(1), pp e48979-e48979
09 Jan 2013
PMID: 23326304
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host's inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.84). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.
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Details
- Title
- Gene Expression-Based Classifiers Identify Staphylococcus aureus Infection in Mice and Humans
- Creators
- Sun Hee Ahn - Duke UniversityEphraim L. Tsalik - Duke University Health SystemDerek D. Cyr - Duke UniversityYurong Zhang - Duke UniversityJennifer C. van Velkinburgh - van Velkinburgh Initiat Collaborat BioMed Res, Santa Fe, NM USARaymond J. Langley - Lovelace Respiratory Research InstituteSeth W. Glickman - University of North Carolina at Chapel HillCharles B. Cairns - College Station Medical CenterAimee K. Zaas - Duke UniversityEmanuel P. Rivers - Henry Ford HospitalRonny M. Otero - Henry Ford HospitalTim Veldman - Duke UniversityStephen F. Kingsmore - Children's Mercy HospitalJoseph Lucas - Duke UniversityChristopher W. Woods - Duke UniversityGeoffrey S. Ginsburg - Duke UniversityVance G. Fowler - Duke University
- Publication Details
- PloS one, v 8(1), pp e48979-e48979
- Publisher
- Public Library Science
- Number of pages
- 16
- Grant note
- Pfizer Wallace H. Coulter Foundation Novartis Pharmaceuticals; Novartis Theravance Novartis Vaccines and Diagnostics, Inc. Cubist Pharmaceuticals R01-AI068804; K24-AI093969; 5U01AI066569-05; 3U01AI066569-05S1 / National Institute of Allergy and Infectious Diseases; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID) Merck; Merck & Company Novartis Alere Corporation National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA Advance Liquid Logic Astellas Pharma US; Astellas Pharmaceuticals Veterans Affairs Career Development Award MedImmune; AstraZeneca; Medimmune Cerexa Roche Molecular Diagnostics Agennix AG
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- College of Medicine
- Web of Science ID
- WOS:000313551500002
- Scopus ID
- 2-s2.0-84872175208
- Other Identifier
- 991021448047704721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Immunology