ArticleGastro hep advances2022
A 'Multiomic' Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019.
Article in Gastro hep advances, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Multi-Omics Signatures of Periodontitis and Periodontal Therapy on the Oral and Gut Microbiome.Journal of periodontal research · 2025Article
- 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
- The role of salivary metabolomics in chronic periodontitis: bridging oral and systemic diseases.Metabolomics : Official journal of the Metabolomic Society · 2025Review
- LongitudinalViruses · 2024Article
- Mass Spectrometry-Based Metabolomics Reveals a Salivary Signature for Low-Severity COVID-19.International journal of molecular sciences · 2024Article
- Saliva, Plasma, and Multifluid Metabolomic Signatures of Periodontal Disease, Type 2 Diabetes Progression, and Markers of Glycemia and Dyslipidemia Among Puerto Rican Adults With Overweight and Obesity.Journal of the American Heart Association · 2024Article
- Critical Factors in Sample Collection and Preparation for Clinical Metabolomics of Underexplored Biological Specimens.Metabolites · 2024Review
- Electronic Tongue for Direct Assessment of SARS-CoV-2-Free and Infected Human Saliva-A Feasibility Study.Biosensors · 2023Article
- Crosstalk between COVID-19 Infection and Kidney Diseases: A Review on the Metabolomic Approaches.Vaccines · 2023Review
- An integrated analysis and comparison of serum, saliva and sebum for COVID-19 metabolomics.Scientific reports · 2022Article
- Untargeted saliva metabolomics by liquid chromatography-Mass spectrometry reveals markers of COVID-19 severity.PloS one · 2022Article
- Improving the Diagnostic Potential of Extracellular miRNAs Coupled to Multiomics Data by Exploiting the Power of Artificial Intelligence.Frontiers in microbiology · 2022Article
- Opioid-Use, COVID-19 Infection, and Their Neurological Implications.Frontiers in neurology · 2022Review
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Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsThe SARS-CoV-2 pandemic has overwhelmed the treatment capacity of the health care systems during the highest viral diffusion rate. Patients reaching the emergency department had to be either hospitalized (inpatients) or discharged (outpatients). Still, the decision was taken based on the individual assessment of the actual clinical condition, without specific biomarkers to predict future improvement or deterioration, and discharged patients often returned to the hospital for aggravation of their condition. Here, we have developed a new combined approach of omics to identify factors that could distinguish coronavirus disease 19 (COVID-19) inpatients from outpatients.
methodsSaliva and blood samples were collected over the course of two observational cohort studies. By using machine learning approaches, we compared salivary metabolome of 50 COVID-19 patients with that of 270 healthy individuals having previously been exposed or not to SARS-CoV-2. We then correlated the salivary metabolites that allowed separating COVID-19 inpatients from outpatients with serum biomarkers and salivary microbiota taxa differentially represented in the two groups of patients.
resultsWe identified nine salivary metabolites that allowed assessing the need of hospitalization. When combined with serum biomarkers, just two salivary metabolites (myo-inositol and 2-pyrrolidineacetic acid) and one serum protein, chitinase 3-like-1 (CHI3L1), were sufficient to separate inpatients from outpatients completely and correlated with modulated microbiota taxa. In particular, we found
conclusionThis is a proof of concept that a combined omic analysis can be used to stratify patients independently from COVID-19.
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