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Fecal host biomarkers predicting severity of Clostridioides difficile infection
Makan Golizeh, … , Momar Ndao, Donald C. Vinh
Makan Golizeh, … , Momar Ndao, Donald C. Vinh
Published November 24, 2020
Citation Information: JCI Insight. 2021;6(1):e142976. https://doi.org/10.1172/jci.insight.142976.
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Research Article Infectious disease Inflammation

Fecal host biomarkers predicting severity of Clostridioides difficile infection

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Abstract

Clostridioides difficile is a major cause of health care–associated diarrhea. Severity ranges from mild to life-threatening, but this variability remains poorly understood. Microbiologic diagnosis of C. difficile infection (CDI) is straightforward but offers little insight into the patient’s prognosis or into pathophysiologic determinants of clinical trajectory. The aim of this study was to discover host-derived, CDI-specific fecal biomarkers involved in disease severity. Subjects without and with CDI diarrhea were recruited. CDI severity was based on Infectious Diseases Society of America/Society for Healthcare Epidemiology of America criteria. We developed a liquid chromatography tandem mass spectrometry approach to identify host-derived protein biomarkers from stool and applied it to diagnostic samples for cohort-wise comparison (CDI-negative vs. nonsevere CDI vs. severe CDI). Selected biomarkers were orthogonally confirmed and subsequently verified in a CDI mouse model. We identified a protein signature from stool, consisting of alpha-2-macroglobulin (A2MG), matrix metalloproteinase-7 (MMP-7), and alpha-1-antitrypsin (A1AT), that not only discriminates CDI-positive samples from non-CDI ones but also is potentially associated with disease severity. In the mouse model, this signature with the murine homologs of the corresponding proteins was also identified. A2MG, MMP-7, and A1AT serve as biomarkers in patients with CDI and define novel components of the host response that may determine disease severity.

Authors

Makan Golizeh, Kaitlin Winter, Lucie Roussel, Marija Landekic, Mélanie Langelier, Vivian G. Loo, Momar Ndao, Donald C. Vinh

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Usage data is cumulative from November 2020 through March 2021.

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PDF 249 0
Figure 24 0
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Citation downloads 29 0
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