ArticleJCI insight2021
Fecal host biomarkers predicting severity of Clostridioides difficile infection.
Article in JCI insight, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Biomarkers for Early Severity Prediction inMedicina (Kaunas, Lithuania) · 2026Review
- Case report of clostridium difficile infection after rectal resection with ileostomy.World journal of surgical oncology · 2025Article
- Defining the black box: a narrative review of factors associated with adverse outcomes from severeTherapeutic advances in gastroenterology · 2021Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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