Mass Spectrometry-Based Metabolomics Reveals a Salivary Signature for Low-Severity COVID-19

Omics approaches were extensively applied during the coronavirus disease 2019 (COVID-19) pandemic to understand the disease, identify biomarkers with diagnostic and prognostic value, and discover new molecular targets for medications. COVID-19 continues to challenge the healthcare system as the virus mutates, becoming more transmissible or adept at evading the immune system, causing resurgent epidemic waves over the last few years. In this study, we used saliva from volunteers who were negative and positive for COVID-19 when Omicron and its variants became dominant. We applied a direct solid-phase extraction approach followed by non-target metabolomics analysis to identify potential salivary signatures of hospital-recruited volunteers to establish a model for COVID-19 screening. Our model, which aimed to differentiate COVID-19-positive individuals from controls in a hospital setting, was based on 39 compounds and achieved high sensitivity (85%/100%), specificity (82%/84%), and accuracy (84%/92%) in training and validation sets, respectively. The salivary diagnostic signatures were mainly composed of amino acids and lipids and were related to a heightened innate immune antiviral response and an attenuated inflammatory profile. The higher abundance of thyrotropin-releasing hormone in the COVID-19 positive group highlighted the endocrine imbalance in low-severity disease, as first reported here, underscoring the need for further studies in this area.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2024-11-06
DOI
https://doi.org/10.3390/ijms252211899
Citations
1
Primary Topic
SARS-CoV-2 detection and testing
Type
article
Field-Weighted Citation Impact
0.39

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article

Mass Spectrometry-Based Metabolomics Reveals a Salivary Signature for Low-Severity COVID-19

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1 citations
International Journal of Molecular Sciences
SARS-CoV-2 detection and testing
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article

Mass Spectrometry-Based Metabolomics Reveals a Salivary Signature for Low-Severity COVID-19

Pedro Henrique Godoy Sanches, Iasmim Lopes de Lima, Carlos Roberto Brites, M. Borges, Thaís Regiani Cataldi, Caroline Pais de Carvalho, Andréia M. Porcari, Alane Beatriz Vermelho, Thiago C. Canevari, Natália Angelo da Silva Miyaguti, Alex Silva, Marcos N. Eberlin, Felipe Raposo Passos Mansoldo, Jonas Ribeiro da Rosa, Alexandre Rodrigues Silva, Sara Nunes, Wellisson Vilarindo Oliveira
article en
1 citations

Abstract

Omics approaches were extensively applied during the coronavirus disease 2019 (COVID-19) pandemic to understand the disease, identify biomarkers with diagnostic and prognostic value, and discover new molecular targets for medications. COVID-19 continues to challenge the healthcare system as the virus mutates, becoming more transmissible or adept at evading the immune system, causing resurgent epidemic waves over the last few years. In this study, we used saliva from volunteers who were negative and positive for COVID-19 when Omicron and its variants became dominant. We applied a direct solid-phase extraction approach followed by non-target metabolomics analysis to identify potential salivary signatures of hospital-recruited volunteers to establish a model for COVID-19 screening. Our model, which aimed to differentiate COVID-19-positive individuals from controls in a hospital setting, was based on 39 compounds and achieved high sensitivity (85%/100%), specificity (82%/84%), and accuracy (84%/92%) in training and validation sets, respectively. The salivary diagnostic signatures were mainly composed of amino acids and lipids and were related to a heightened innate immune antiviral response and an attenuated inflammatory profile. The higher abundance of thyrotropin-releasing hormone in the COVID-19 positive group highlighted the endocrine imbalance in low-severity disease, as first reported here, underscoring the need for further studies in this area.

International Journal of Molecular SciencesVol. 25(22)
Universidade Federal do Rio de Janeiro (BR), Universidade Federal da Bahia (BR), Universidade de São Paulo (BR), Universidade Presbiteriana Mackenzie (BR), Complexo Hospitalar Universitário Professor Edgard Santos (BR), Universidade São Francisco (BR)
Fundação de Amparo à Pesquisa do Estado de São Paulo, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico
Good health and well-being
Openalex Percentile: Top 35%
SARS-CoV-2 detection and testing
0.39
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