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Gut microbiota diversity and C-Reactive Protein are predictors of disease severity in COVID-19 patients (preprint)
biorxiv; 2021.
Preprint
in English
| bioRxiv | ID: ppzbmed-10.1101.2021.04.20.440658
ABSTRACT
Risk factors for COVID-19 disease severity are still poorly understood. Considering the pivotal role of gut microbiota on host immune and inflammatory functions, we investigated the association between changes in gut microbiota composition and the clinical severity of COVID-19. We conducted a multicentre cross-sectional study prospectively enrolling 115 COVID-19 patients categorized according to 1) WHO Clinical Progression Scale - mild 19 (16.5%), moderate 37 (32.2%) or severe 59 (51.3%); and 2) location of recovery from COVID-19 - ambulatory 14 (household isolation; 12.2%), hospitalized in ward 40 (34.8%) or intensive care unit 61 (53.0%). Gut microbiota analysis was performed through 16S rRNA gene sequencing and data obtained was further related with clinical parameters of COVID-19 patients. Risk factors for COVID-19 severity were identified by univariate and multivariable logistic regression models. In comparison with mild COVID-19 patients, the gut microbiota of moderate and severe patients has a) lower Firmicutes/Bacteroidetes ratio, b) higher abundance of Proteobacteria; and c) lower abundance of beneficial butyrate-producing bacteria such as Roseburia and Lachnospira genera. Multivariable regression analysis showed that Shannon index diversity (odds ratio [OR] 2.85 [95% CI 1.09-7.41]; p=0.032) and C-Reactive Protein (OR 3.45 [95% CI 1.33-8.91]; p=0.011) were risk factors for COVID-19 severe disease (a score of 6 or higher in WHO clinical progression scale). In conclusion, our results demonstrated that hospitalised moderate and severe COVID-19 patients have microbial signatures of gut dysbiosis and for the first time, the gut microbiota diversity is pointed out as a prognostic biomarker for COVID-19 disease severity.
Full text:
Available
Collection:
Preprints
Database:
bioRxiv
Main subject:
Dysbiosis
/
COVID-19
Language:
English
Year:
2021
Document Type:
Preprint
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