AUTHOR=Oliveira Lucas Barbosa , Mwangi Victor Irungu , Sartim Marco Aurélio , Delafiori Jeany , Sales Geovana Manzan , de Oliveira Arthur Noin , Busanello Estela Natacha Brandt , Val Fernando Fonseca de Almeida e , Xavier Mariana Simão , Costa Fabio Trindade , Baía-da-Silva Djane Clarys , Sampaio Vanderson de Souza , de Lacerda Marcus Vinicius Guimarães , Monteiro Wuelton Marcelo , Catharino Rodrigo Ramos , de Melo Gisely Cardoso 

TITLE=Metabolomic Profiling of Plasma Reveals Differential Disease Severity Markers in COVID-19 Patients

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2022.844283

DOI=10.3389/fmicb.2022.844283

ISSN=1664-302X

ABSTRACT=The severity, disabilities, and lethality by Coronavirus 2019 (COVID-19) disease have dumbfounded the entire world on an unprecedented scale. This consequently generated interest in understanding the clinical history of COVID-19, particularly the classification of severity and early prediction on prognosis. Metabolomics is a powerful tool in identifying metabolite signatures when profiling parasitic, metabolic, and microbial diseases. This study undertook a metabolomic approach to identify potential metabolic signatures to discriminate severe from non-severe COVID-19. As a secondary objective, we aimed to identify whether clinical and laboratory data from the severe and non-severe COVID-19 patients were compatible with the metabolomics findings. Analysis of samples revealed that 43 metabolites from 9 classes indicated COVID-19 severity: 29 metabolites for non-severe and 14 metabolites for severe disease. Metabolites from porphyrin and purine pathways were significantly increased in the severe group, suggesting they could serve as potential prognostic biomarkers.
Pathway analysis identified 8 metabolomic pathways associated with the 43 discriminating metabolites. Pathway analysis revealed that although there were impactful changes in the glycerophospholipid and porphyrin metabolism in the context of COVID-19 severity, glycerophospholipid, and linoleic acid metabolism had significant changes (p=0.025 and p=0.035, respectively). Our results indicate that these metabolomics-based markers could have prognostic and diagnostic potential in managing and understanding the evolution of COVID-19 disease.