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A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019

BACKGROUND AND AIMS: The 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 bas...

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Autores principales: Pozzi, Chiara, Levi, Riccardo, Braga, Daniele, Carli, Francesco, Darwich, Abbass, Spadoni, Ilaria, Oresta, Bianca, Dioguardi, Carola Conca, Peano, Clelia, Ubaldi, Leonardo, Angelotti, Giovanni, Bottazzi, Barbara, Garlanda, Cecilia, Desai, Antonio, Voza, Antonio, Azzolini, Elena, Cecconi, Maurizio, Mantovani, Alberto, Penna, Giuseppe, Barbieri, Riccardo, Politi, Letterio S., Rescigno, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Inc. on behalf of the AGA Institute. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818445/
https://www.ncbi.nlm.nih.gov/pubmed/35174369
http://dx.doi.org/10.1016/j.gastha.2021.12.006
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author Pozzi, Chiara
Levi, Riccardo
Braga, Daniele
Carli, Francesco
Darwich, Abbass
Spadoni, Ilaria
Oresta, Bianca
Dioguardi, Carola Conca
Peano, Clelia
Ubaldi, Leonardo
Angelotti, Giovanni
Bottazzi, Barbara
Garlanda, Cecilia
Desai, Antonio
Voza, Antonio
Azzolini, Elena
Cecconi, Maurizio
Mantovani, Alberto
Penna, Giuseppe
Barbieri, Riccardo
Politi, Letterio S.
Rescigno, Maria
author_facet Pozzi, Chiara
Levi, Riccardo
Braga, Daniele
Carli, Francesco
Darwich, Abbass
Spadoni, Ilaria
Oresta, Bianca
Dioguardi, Carola Conca
Peano, Clelia
Ubaldi, Leonardo
Angelotti, Giovanni
Bottazzi, Barbara
Garlanda, Cecilia
Desai, Antonio
Voza, Antonio
Azzolini, Elena
Cecconi, Maurizio
Mantovani, Alberto
Penna, Giuseppe
Barbieri, Riccardo
Politi, Letterio S.
Rescigno, Maria
author_sort Pozzi, Chiara
collection PubMed
description BACKGROUND AND AIMS: The 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. METHODS: Saliva 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. RESULTS: We 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 Corynebacterium 1 to be overrepresented in inpatients, whereas Actinomycetaceae F0332, Candidatus Saccharimonas, and Haemophilus were all underrepresented in the hospitalized population. CONCLUSION: This is a proof of concept that a combined omic analysis can be used to stratify patients independently from COVID-19.
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spelling pubmed-88184452022-02-07 A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019 Pozzi, Chiara Levi, Riccardo Braga, Daniele Carli, Francesco Darwich, Abbass Spadoni, Ilaria Oresta, Bianca Dioguardi, Carola Conca Peano, Clelia Ubaldi, Leonardo Angelotti, Giovanni Bottazzi, Barbara Garlanda, Cecilia Desai, Antonio Voza, Antonio Azzolini, Elena Cecconi, Maurizio Mantovani, Alberto Penna, Giuseppe Barbieri, Riccardo Politi, Letterio S. Rescigno, Maria Gastro Hep Adv Original Research—Basic BACKGROUND AND AIMS: The 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. METHODS: Saliva 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. RESULTS: We 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 Corynebacterium 1 to be overrepresented in inpatients, whereas Actinomycetaceae F0332, Candidatus Saccharimonas, and Haemophilus were all underrepresented in the hospitalized population. CONCLUSION: This is a proof of concept that a combined omic analysis can be used to stratify patients independently from COVID-19. The Authors. Published by Elsevier Inc. on behalf of the AGA Institute. 2022 2022-02-07 /pmc/articles/PMC8818445/ /pubmed/35174369 http://dx.doi.org/10.1016/j.gastha.2021.12.006 Text en © 2022 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Original Research—Basic
Pozzi, Chiara
Levi, Riccardo
Braga, Daniele
Carli, Francesco
Darwich, Abbass
Spadoni, Ilaria
Oresta, Bianca
Dioguardi, Carola Conca
Peano, Clelia
Ubaldi, Leonardo
Angelotti, Giovanni
Bottazzi, Barbara
Garlanda, Cecilia
Desai, Antonio
Voza, Antonio
Azzolini, Elena
Cecconi, Maurizio
Mantovani, Alberto
Penna, Giuseppe
Barbieri, Riccardo
Politi, Letterio S.
Rescigno, Maria
A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019
title A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019
title_full A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019
title_fullStr A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019
title_full_unstemmed A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019
title_short A ‘Multiomic’ Approach of Saliva Metabolomics, Microbiota, and Serum Biomarkers to Assess the Need of Hospitalization in Coronavirus Disease 2019
title_sort ‘multiomic’ approach of saliva metabolomics, microbiota, and serum biomarkers to assess the need of hospitalization in coronavirus disease 2019
topic Original Research—Basic
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818445/
https://www.ncbi.nlm.nih.gov/pubmed/35174369
http://dx.doi.org/10.1016/j.gastha.2021.12.006
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