Abstract

Background

Severe COVID-19 is a disease characterized by profound dysregulation of the innate immune system. There is a need to identify highly reliable prognostic biomarkers that can be rapidly assessed in body fluids for early identification of patients at higher risk for hospitalization and/or death. This study aimed to assess whether differential gene expression of immune response molecules and cellular enzymes, detected in saliva samples of COVID-19 patients, occurs according to disease severity staging.

Methods

In this cross-sectional study, subjects with a COVID-19 diagnosis were classified as having mild, moderate, or severe disease based on clinical features. Transcripts of genes encoding 6 biomarkers, IL-1β, IL-6, IL-10, C-reactive protein, IDO1 and ACE2, were measured by RT‒qPCR in saliva samples of patients and COVID-19-free individuals.

Results

The gene expression levels of all 6 biomarkers in saliva were significantly increased in severe disease patients compared to mild/moderate disease patients and healthy controls. A significant strong inverse relationship between oxemia and the level of expression of the 6 biomarkers (Spearman’s correlation coefficient between -0.692 and -0.757; p < 0.001) was found.

Conclusions

Biomarker gene expression determined in saliva samples still needs to be validated as a potentially valuable predictor of severe clinical outcomes early at the onset of COVID-19 symptoms.

Details

Title
Differential expression of biomarkers in saliva related to SARS-CoV-2 infection in patients with mild, moderate and severe COVID-19
Author
Verdiguel-Fernández, Lázaro; Arredondo-Hernández, Rene; Jesús Andrés Mejía-Estrada; Ortiz, Adolfo; Verdugo-Rodríguez, Antonio; Orduña, Patricia; Ponce de León-Rosales, Samuel; Calva, Juan José; López-Vidal, Yolanda
Pages
1-12
Section
Research
Publication year
2023
Publication date
2023
Publisher
BioMed Central
e-ISSN
14712334
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2865358535
Copyright
© 2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.