ArticlePloS one2022
Untargeted saliva metabolomics by liquid chromatography-Mass spectrometry reveals markers of COVID-19 severity.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry.Metabolism: clinical and experimental · 2022Pooled it
- Advancements and Challenges in Salivary Metabolomics for Early Detection and Monitoring of Systemic Diseases.MedComm · 2025Review
- Analyses of Saliva Metabolome Reveal Patterns of Metabolites That Differentiate SARS-CoV-2 Infection and COVID-19 Disease Severity.Metabolites · 2025Article
- Advantages of Metabolomics-Based Multivariate Machine Learning to Predict Disease Severity: Example of COVID.International journal of molecular sciences · 2024Article
- Metabolomic Insights into COVID-19 Severity: A Scoping Review.Metabolites · 2024Article
- Mass Spectrometry-Based Metabolomics Reveals a Salivary Signature for Low-Severity COVID-19.International journal of molecular sciences · 2024Article
- Novel COVID-19 biomarkers identified through multi-omics data analysis: N-acetyl-4-O-acetylneuraminic acid, N-acetyl-L-alanine, N-acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate.Internal and emergency medicine · 2024Article
- Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens.Metabolites · 2024Review
- Article
- Persistent immune and clotting dysfunction detected in saliva and blood plasma after COVID-19.Heliyon · 2023Article
- Diagnostic, Prognostic and Mechanistic Biomarkers of COVID-19 Identified by Mass Spectrometric Metabolomics.Metabolites · 2023Review
- Crosstalk between COVID-19 Infection and Kidney Diseases: A Review on the Metabolomic Approaches.Vaccines · 2023Review
- Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19.Frontiers in molecular biosciences · 2023Review
- Saliva metabolomic profile of COVID-19 patients associates with disease severity.Metabolomics : Official journal of the Metabolomic Society · 2022Article
- A colorimetric electronic tongue for point-of-care detection of COVID-19 using salivary metabolites.Talanta · 2022Article
- An integrated analysis and comparison of serum, saliva and sebum for COVID-19 metabolomics.Scientific reports · 2022Article
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Authors and funding
15 authors.
Funding
Abstract
backgroundThe COVID-19 pandemic is likely to represent an ongoing global health issue given the potential for new variants, vaccine escape and the low likelihood of eliminating all reservoirs of the disease. Whilst diagnostic testing has progressed at a fast pace, the metabolic drivers of outcomes-and whether markers can be found in different biofluids-are not well understood. Recent research has shown that serum metabolomics has potential for prognosis of disease progression. In a hospital setting, collection of saliva samples is more convenient for both staff and patients, and therefore offers an alternative sampling matrix to serum.
methodsSaliva samples were collected from hospitalised patients with clinical suspicion of COVID-19, alongside clinical metadata. COVID-19 diagnosis was confirmed using RT-PCR testing, and COVID-19 severity was classified using clinical descriptors (respiratory rate, peripheral oxygen saturation score and C-reactive protein levels). Metabolites were extracted and analysed using high resolution liquid chromatography-mass spectrometry, and the resulting peak area matrix was analysed using multivariate techniques.
resultsPositive percent agreement of 1.00 between a partial least squares-discriminant analysis metabolomics model employing a panel of 6 features (5 of which were amino acids, one that could be identified by formula only) and the clinical diagnosis of COVID-19 severity was achieved. The negative percent agreement with the clinical severity diagnosis was also 1.00, leading to an area under receiver operating characteristics curve of 1.00 for the panel of features identified.
conclusionsIn this exploratory work, we found that saliva metabolomics and in particular amino acids can be capable of separating high severity COVID-19 patients from low severity COVID-19 patients. This expands the atlas of COVID-19 metabolic dysregulation and could in future offer the basis of a quick and non-invasive means of sampling patients, intended to supplement existing clinical tests, with the goal of offering timely treatment to patients with potentially poor outcomes.
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