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Immunometabolic signatures predict risk of progression to sepsis in COVID-19

  • Ana Sofía Herrera Van Oostdam
    ,
  • Julio E. Castañeda-Delgado
    ,
  • Juan José Oropeza-Valdez
    ,
  • Juan Carlos Borrego
    ,
  • ,
  • Jiamin Zheng
  • Universidad Autonoma de San Luis Potosi
    ,
  • Instituto Mexicano del Seguro Social
    ,
  • Consejo Nacional de Ciencia y Tecnologia Mexico
    ,
  • ,
  • University of Alberta
    ,
  • Universidad Autonoma de Zacatecas
Research Output:
Contribution to journal
Article
Peer-review

Open access

Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Publication metrics

Metrics

SciVal
FWCI
1.39
SciVal
Author count
16
SciVal
Paper percentile
80
SciVal
Citations
38
Scopus
Citations

Abstract

Viral sepsis has been proposed as an accurate term to describe all multisystemic dysregulations and clinical findings in severe and critically ill COVID-19 patients. The adoption of this term may help the implementation of more accurate strategies of early diagnosis, prognosis, and in-hospital treatment. We accurately quantified 110 metabolites using targeted metabolomics, and 13 cytokines/chemokines in plasma samples of 121 COVID-19 patients with different levels of severity, and 37 non-COVID-19 individuals. Analyses revealed an integrated host-dependent dysregulation of inflammatory cytokines, neutrophil activation chemokines, glycolysis, mitochondrial metabolism, amino acid metabolism, polyamine synthesis, and lipid metabolism typical of sepsis processes distinctive of a mild disease. Dysregulated metabolites and cytokines/chemokines showed differential correlation patterns in mild and critically ill patients, indicating a crosstalk between metabolism and hyperinflammation. Using multivariate analysis, powerful models for diagnosis and prognosis of COVID-19 induced sepsis were generated, as well as for mortality prediction among septic patients. A metabolite panel made of kynurenine/tryptophan ratio, IL-6, LysoPC a C18:2, and phenylalanine discriminated non-COVID-19 from sepsis patients with an area under the curve (AUC (95%CI)) of 0.991 (0.986–0.995), with sensitivity of 0.978 (0.963–0.992) and specificity of 0.920 (0.890–0.949). The panel that included C10:2, IL-6, NLR, and C5 discriminated mild patients from sepsis patients with an AUC (95%CI) of 0.965 (0.952–0.977), with sensitivity of 0.993(0.984–1.000) and specificity of 0.851 (0.815–0.887). The panel with citric acid, LysoPC a C28:1, neutrophil-lymphocyte ratio (NLR) and kynurenine/tryptophan ratio discriminated severe patients from sepsis patients with an AUC (95%CI) of 0.829 (0.800–0.858), with sensitivity of 0.738 (0.695–0.781) and specificity of 0.781 (0.735–0.827). Septic patients who survived were different from those that did not survive with a model consisting of hippuric acid, along with the presence of Type II diabetes, with an AUC (95%CI) of 0.831 (0.788–0.874), with sensitivity of 0.765 (0.697–0.832) and specificity of 0.817 (0.770–0.865).

Publication Information

Output type

Research Output:
Contribution to journal
Article
Peer-review

Original language

English

Article number

e0256784

Pages from-to (Number of pages)

Pages e0256784

Journal (Volume, Issue Number)

PLoS One (Volume 16, Issue 8 August)

Publication milestones

  • Published - 08/2021

Publication status

Published - 08/2021

ISSN

1932-6203

Publication IDs

  • Scopus: 85114034884
  • PubMed: 34460840