Mohammad H Semreen1,2, Rabih Halwani3,4,5, Narjes Saheb Sharif-Askari1, Nelson Cruz Soares1,6, Hajer A Mohamed1,6, Fatemeh Saheb Sharif-Askari1, Hawra Ali Hussain Alsayed7, Hamza Al-Hroub1, Laila Salameh8,9, Rufaida Satti Osman8, Bassam Mahboub8,9, Qutayba Hamid1,9,10. 1. Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE. 2. College of Pharmacy, University of Sharjah, Sharjah, UAE. 3. Research Institute of Medical & Health Sciences, University of Sharjah, Sharjah, UAE. rhalwani@sharjah.ac.ae. 4. Department of Clinical Sciences, College of Medicine, University of Sharjah, P.O. Box 27272, Sharjah, UAE. rhalwani@sharjah.ac.ae. 5. Prince Abdullah Ben Khaled Celiac Disease Research Chair, Department of Pediatrics, Faculty of Medicine, King Saud University, Riyadh, Saudi Arabia. rhalwani@sharjah.ac.ae. 6. Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah, UAE. 7. Pharmacy Department, Dubai Health Authority, Dubai, UAE. 8. Rashid Hospital, Dubai Health Authority, Dubai, UAE. 9. Department of Clinical Sciences, College of Medicine, University of Sharjah, P.O. Box 27272, Sharjah, UAE. 10. Meakins-Christie Laboratories, McGill University, Montreal, QC, Canada.
Abstract
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.
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.
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