Saliva metabolomic profile of COVID-19 patients associates with disease severity

Introduction Coronavirus disease 2019 (COVID-19) is strongly linked to dysregulation of various molecular, cellular, and physiological processes that change abundance of different biomolecules including metabolites that may be ultimately used as biomarkers for disease progression and severity. It is important at early stage to readily distinguish those patients that are likely to progress to moderate and severe stages. Objectives This study aimed to investigate the utility of saliva and plasma metabolomic profiles as a potential parameter for risk stratifying COVID-19 patients. Method LC-MS/MS-based untargeted metabolomics were used to profile the changes in saliva and plasma metabolomic profiles of COVID-19 patients with different severities. Results Saliva and plasma metabolites were screened in 62 COVID-19 patients and 18 non-infected controls. The COVID-19 group included 16 severe, 15 moderate, 16 mild, and 15 asymptomatic cases. Thirty-six differential metabolites were detected in COVID-19 versus control comparisons. SARS-CoV-2 induced metabolic derangement differed with infection severity. The metabolic changes were identified in saliva and plasma, however, saliva showed higher intensity of metabolic changes. Levels of saliva metabolites such as sphingosine and kynurenine were significantly different between COVID-19 infected and non-infected individuals; while linoleic acid and Alpha-ketoisovaleric acid were specifically increased in severe compared to non-severe patients. As expected, the two prognostic biomarkers of C-reactive protein and D-dimer were negatively correlated with sphingosine and 5-Aminolevulinic acid, and positively correlated with l-Tryptophan and l-Kynurenine. Conclusion Saliva disease-specific and severity-specific metabolite could be employed as potential COVID-19 diagnostic and prognostic biomarkers.

Automated summary

This study investigated the utility of saliva and plasma metabolomic profiles as potential parameters for risk stratifying COVID-19 patients. LC-MS/MS-based untargeted metabolomics were used to profile changes in saliva and plasma metabolites of COVID-19 patients, revealing significant differences in metabolites between infected and non-infected individuals. Saliva-specific metabolites could serve as diagnostic and prognostic biomarkers for COVID-19.