UMass Chan Medical School Faculty Publications

UMMS Affiliation

Department of Microbiology and Physiological Systems; Program of Microbiome Dynamics; Department of Medicine, Division of Infectious Diseases and Immunology; Department of Internal Medicine; Department of Pediatrics; School of Medicine; Graduate School of Biomedical Sciences

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Article Preprint


Bacteria | Environmental Public Health | Immunology of Infectious Disease | Immunopathology | Infectious Disease | Medical Microbiology | Microbiology | Virus Diseases


The reason for the striking differences in clinical outcomes of SARS-CoV-2 infected patients is still poorly understood. While most recover, a subset of people become critically ill and succumb to the disease. Thus, identification of biomarkers that can predict the clinical outcomes of COVID-19 disease is key to help prioritize patients needing urgent treatment. Given that an unbalanced gut microbiome is a reflection of poor health, we aim to identify indicator species that could predict COVID-19 disease clinical outcomes. Here, for the first time and with the largest COVID-19 patient cohort reported for microbiome studies, we demonstrated that the intestinal and oral microbiome make-up predicts respectively with 92% and 84% accuracy (Area Under the Curve or AUC) severe COVID-19 respiratory symptoms that lead to death. The accuracy of the microbiome prediction of COVID-19 severity was found to be far superior to that from training similar models using information from comorbidities often adopted to triage patients in the clinic (77% AUC). Additionally, by combining symptoms, comorbidities, and the intestinal microbiota the model reached the highest AUC at 96%. Remarkably the model training on the stool microbiome found enrichment of Enterococcus faecalis, a known pathobiont, as the top predictor of COVID-19 disease severity. Enterococcus faecalis is already easily cultivable in clinical laboratories, as such we urge the medical community to include this bacterium as a robust predictor of COVID-19 severity when assessing risk stratification of patients in the clinic.


SARS-CoV-2, biomarkers, intestinal and oral microbiome, COVID-19 severity, Enterococcus faecalis, predictor, risk stratification, microbiome prediction

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medRxiv 2021.01.05.20249061; doi: Link to preprint on medRxiv.


This article is a preprint. Preprints are preliminary reports of work that have not been certified by peer review.

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Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.