Validation of a host response test to distinguish bacterial and viral respiratory infection
Emily C. Lydon,
Ricardo Henao,
Thomas W. Burke,
Mert Aydin,
Bradly P. Nicholson,
Seth W. Glickman,
Vance G. Fowler,
Eugenia B. Quackenbush,
Charles B. Cairns,
Stephen F. Kingsmore,
Anja K. Jaehne,
Emanuel P. Rivers,
Raymond J. Langley,
Elizabeth Petzold,
Emily R. Ko,
Micah T. McClain,
Geoffrey S. Ginsburg,
Christopher W. Woods,
Ephraim L. Tsalik
Affiliations
Emily C. Lydon
Duke University School of Medicine, Durham, NC, USA; Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
Ricardo Henao
Duke University Department of Biostatistics and Informatics, Durham, NC, USA
Thomas W. Burke
Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
Mert Aydin
Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
Bradly P. Nicholson
Institute of Medical Research, Durham Veterans Affairs Medical Center, Durham, NC, USA
Seth W. Glickman
University of North Carolina Medical Center, Chapel Hill, NC, USA
Vance G. Fowler
Duke University Department of Medicine, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA
Eugenia B. Quackenbush
University of North Carolina Medical Center, Chapel Hill, NC, USA
Charles B. Cairns
University of North Carolina Medical Center, Chapel Hill, NC, USA; United Arab Emirates University, Al Ain, UAE
Stephen F. Kingsmore
Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
Anja K. Jaehne
Henry Ford Hospital System, Detroit, MI, USA
Emanuel P. Rivers
Henry Ford Hospital System, Detroit, MI, USA
Raymond J. Langley
University of South Alabama Health University Hospital, Mobile, AL, USA
Elizabeth Petzold
Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
Emily R. Ko
Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA; Department of Hospital Medicine, Duke Regional Hospital, Durham, NC 27705, USA
Micah T. McClain
Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA; Durham Veterans Affairs Health Care System, Durham, NC, USA
Geoffrey S. Ginsburg
Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA
Christopher W. Woods
Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA; Durham Veterans Affairs Health Care System, Durham, NC, USA; Co-Corresponding author at: 508 Fulton Street, Service 113,Durham, NC 27710, USA
Ephraim L. Tsalik
Duke University Center for Applied Genomics and Precision Medicine, Durham, NC, USA; Durham Veterans Affairs Health Care System, Durham, NC, USA; Corresponding author at: Duke University Medical Center 102359, Durham, NC 27705, USA.
Background: Distinguishing bacterial and viral respiratory infections is challenging. Novel diagnostics based on differential host gene expression patterns are promising but have not been translated to a clinical platform nor extensively tested. Here, we validate a microarray-derived host response signature and explore performance in microbiology-negative and coinfection cases. Methods: Subjects with acute respiratory illness were enrolled in participating emergency departments. Reference standard was an adjudicated diagnosis of bacterial infection, viral infection, both, or neither. An 87-transcript signature for distinguishing bacterial, viral, and noninfectious illness was measured from peripheral blood using RT-PCR. Performance characteristics were evaluated in subjects with confirmed bacterial, viral, or noninfectious illness. Subjects with bacterial-viral coinfection and microbiologically-negative suspected bacterial infection were also evaluated. Performance was compared to procalcitonin. Findings: 151 subjects with microbiologically confirmed, single-etiology illness were tested, yielding AUROCs 0•85–0•89 for bacterial, viral, and noninfectious illness. Accuracy was similar to procalcitonin (88% vs 83%, p = 0•23) for bacterial vs. non-bacterial infection. Whereas procalcitonin cannot distinguish viral from non-infectious illness, the RT-PCR test had 81% accuracy in making this determination. Bacterial-viral coinfection was subdivided. Among 19 subjects with bacterial superinfection, the RT-PCR test identified 95% as bacterial, compared to 68% with procalcitonin (p = 0•13). Among 12 subjects with bacterial infection superimposed on chronic viral infection, the RT-PCR test identified 83% as bacterial, identical to procalcitonin. 39 subjects had suspected bacterial infection; the RT-PCR test identified bacterial infection more frequently than procalcitonin (82% vs 64%, p = 0•02). Interpretation: The RT-PCR test offered similar diagnostic performance to procalcitonin in some subgroups but offered better discrimination in others such as viral vs. non-infectious illness and bacterial/viral coinfection. Gene expression-based tests could impact decision-making for acute respiratory illness as well as a growing number of other infectious and non-infectious diseases. Keywords: Biomarkers, Gene expression, Respiratory tract infections, Coinfection, Diagnosis, Precision medicine