Metabolites (Mar 2025)

Analyses of Saliva Metabolome Reveal Patterns of Metabolites That Differentiate SARS-CoV-2 Infection and COVID-19 Disease Severity

  • Violeta Larios-Serrato,
  • Natalia Vázquez-Manjarrez,
  • Osbaldo Resendis-Antonio,
  • Nora Rios-Sarabia,
  • Beatriz Meza,
  • Oliver Fiehn,
  • Javier Torres

DOI
https://doi.org/10.3390/metabo15030192
Journal volume & issue
Vol. 15, no. 3
p. 192

Abstract

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Background: The metabolome of COVID-19 patients has been studied sparsely, with most research focusing on a limited number of plasma metabolites or small cohorts. This is the first study to test saliva metabolites in COVID-19 patients in a comprehensive way, revealing patterns significantly linked to disease and severity, highlighting saliva’s potential as a non-invasive tool for pathogenesis or diagnostic studies. Methods: We included 30 asymptomatic subjects with no prior COVID-19 infection or vaccination, 102 patients with mild SARS-CoV-2 infection, and 61 hospitalized patients with confirmed SARS-CoV-2 status. Saliva samples were analyzed using hydrophilic interaction liquid chromatography–mass spectrometry (HILIC-MS/MS) in positive and negative ionization modes. Results: Significant differences in metabolites were identified in COVID-19 patients, with distinct patterns associated with disease severity. Dipeptides such as Val-Glu and Met-Gln were highly elevated in moderate cases, suggesting specific protease activity related to SARS-CoV-2. Acetylated amino acids like N-acetylserine and N-acetylhistidine increased in severe cases. Bacterial metabolites, including muramic acid and indole-3-carboxaldehyde, were higher in mild–moderate cases, indicating that oral microbiota differs according to disease severity. In severe cases, polyamines and organ-damage-related metabolites, such as N-acetylspermine and 3-methylcytidine, were significantly increased. Interestingly, most metabolites that were reduced in moderate cases were elevated in severe cases. Conclusions: Saliva metabolomics offers insightful information that is potentially useful in studying COVID-19 severity and for diagnosis.

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