THE INTESTINAL AND ORAL MICROBIOMES ARE ROBUST PREDICTORS OF COVID-19 SEVERITY THE MAIN PREDICTOR OF COVID-19-RELATED FATALITY
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Abstract
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.
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SciScore for 10.1101/2021.01.05.20249061: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: The Institutional Review Board at the University of Massachusetts Medical School approved this study.
Consent: Informed consent was obtained from all study participants or their health care proxy using RedCap digital signatures to reduce the potential for patient-staff transmission.Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Informed consent was obtained from all study participants or their health care proxy using RedCap digital signatures to reduce the potential for patient-staff transmission. RedCapsuggested: (REDCap, RRID:SCR_0…SciScore for 10.1101/2021.01.05.20249061: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: The Institutional Review Board at the University of Massachusetts Medical School approved this study.
Consent: Informed consent was obtained from all study participants or their health care proxy using RedCap digital signatures to reduce the potential for patient-staff transmission.Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Informed consent was obtained from all study participants or their health care proxy using RedCap digital signatures to reduce the potential for patient-staff transmission. RedCapsuggested: (REDCap, RRID:SCR_003445)Taxonomic assignments were made using BLASTN against the NCBI refseq rna database. BLASTNsuggested: (BLASTN, RRID:SCR_001598)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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SciScore for 10.1101/2021.01.05.20249061: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement The Institutional Review Board at the University of Massachusetts Medical School approved this study. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources ) Severe (n=31) p-value Demographics Age (years) BMI Female (%) Race White (%) Black or African American (%) Hispanic or Latino (%) Asian (% Race Whitesuggested: NoneSoftware and Algorithms Sentences Resources Informed consent was obtained from all study … SciScore for 10.1101/2021.01.05.20249061: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement The Institutional Review Board at the University of Massachusetts Medical School approved this study. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources ) Severe (n=31) p-value Demographics Age (years) BMI Female (%) Race White (%) Black or African American (%) Hispanic or Latino (%) Asian (% Race Whitesuggested: NoneSoftware and Algorithms Sentences Resources Informed consent was obtained from all study participants or their health care proxy using RedCap digital signatures to reduce the potential for patient-staff transmission. RedCapsuggested: (REDCap, RRID:SCR_003445)Taxonomic assignments were made using BLASTN against the NCBI refseq rna database. BLASTNsuggested: (BLASTN, RRID:SCR_001598)For microbial abundances we used the Amplicon Sequence Variant (ASV) counts normalized using DeSeq2 43. DeSeq2suggested: (DESeq2, RRID:SCR_015687)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
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