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Publications

Journal Article Epublish 23 citations

PubMed: 35572676 DOI: 10.3389/fmicb.2022.844283

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

Front Microbiol 13:844283

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

Affiliations

  • Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil.
  • Programas de Pós-Graduação em Imunologia Básica e Aplicada (PPGIBA), Universidade Federal do Amazonas (UFAM), Manaus, Brazil.
  • Pró-reitoria de Pesquisa e Pós-graduação, Universidade Nilton Lins, Manaus, Brazil.
  • Laboratório Innovare de Biomarcadores, Faculdade de Ciências Farmacêuticas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
  • Fundação de Medicina Tropical Heitor Vieira Dourado (FMT-HVD), Manaus, Brazil.
  • Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
  • Instituto de Pesquisas Leônidas & Maria Deane (FIOCRUZ-Amazonas), Manaus, Brazil.

Abstract

The severity, disabilities, and lethality caused by the coronavirus 2019 (COVID-19) disease have dumbfounded the entire world on an unprecedented scale. The multifactorial aspect of the infection has 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 for identifying metabolite signatures when profiling parasitic, metabolic, and microbial diseases. This study undertook a metabolomic approach to identify potential metabolic signatures to discriminate severe COVID-19 from non-severe COVID-19. The secondary aim was to determine whether the clinical and laboratory data from the severe and non-severe COVID-19 patients were compatible with the metabolomic findings. Metabolomic 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. The metabolites from porphyrin and purine pathways were significantly elevated in the severe disease group, suggesting that they could be potential prognostic biomarkers. Elevated levels of the cholesteryl ester CE (18:3) in non-severe patients matched the significantly different blood cholesterol components (total cholesterol and HDL, both < 0.001) that were detected. Pathway analysis identified 8 metabolomic pathways associated with the 43 discriminating metabolites. Metabolomic pathway analysis revealed that COVID-19 affected glycerophospholipid and porphyrin metabolism but significantly affected the glycerophospholipid and linoleic acid metabolism pathways ( = 0.025 and = 0.035, respectively). Our results indicate that these metabolomics-based markers could have prognostic and diagnostic potential when managing and understanding the evolution of COVID-19.

MeSH

Infections, Plasma, Prognosis, Cholesterol, Metabolomics, Covid-19, Sars-Cov-2

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