Data_Sheet_1_Untargeted plasma metabolomic fingerprinting highlights several biomarkers for the diagnosis and prognosis of coronavirus disease 19.xlsx

ObjectivesThe COVID-19 pandemic has been a serious worldwide public health crisis since 2020 and is still challenging healthcare systems. New tools for the prognosis and diagnosis of COVID-19 patients remain important issues.DesignHere, we studied the metabolome of plasma samples of COVID-19 patients for the identification of prognosis biomarkers.PatientsPlasma samples of eighty-six SARS-CoV-2-infected subjects and 24 healthy controls were collected during the first peak of the COVID-19 pandemic in France in 2020.Main resultsPlasma metabolome fingerprinting allowed the successful discrimination of healthy controls, mild SARS-CoV-2 subjects, and moderate and severe COVID-19 patients at hospital admission. We found a strong effect of SARS-CoV-2 infection on the plasma metabolome in mild cases. Our results revealed that plasma lipids and alterations in their saturation level are important biomarkers for the detection of the infection. We also identified deoxy-fructosyl-amino acids as new putative plasma biomarkers for SARS-CoV-2 infection and COVID-19 severity. Finally, our results highlight a key role for plasma levels of tryptophan and kynurenine in the symptoms of COVID-19 patients.ConclusionOur results showed that plasma metabolome profiling is an efficient tool for the diagnosis and prognosis of SARS-CoV-2 infection.</p

Presentation_1_Untargeted plasma metabolomic fingerprinting highlights several biomarkers for the diagnosis and prognosis of coronavirus disease 19.pptx

ObjectivesThe COVID-19 pandemic has been a serious worldwide public health crisis since 2020 and is still challenging healthcare systems. New tools for the prognosis and diagnosis of COVID-19 patients remain important issues.DesignHere, we studied the metabolome of plasma samples of COVID-19 patients for the identification of prognosis biomarkers.PatientsPlasma samples of eighty-six SARS-CoV-2-infected subjects and 24 healthy controls were collected during the first peak of the COVID-19 pandemic in France in 2020.Main resultsPlasma metabolome fingerprinting allowed the successful discrimination of healthy controls, mild SARS-CoV-2 subjects, and moderate and severe COVID-19 patients at hospital admission. We found a strong effect of SARS-CoV-2 infection on the plasma metabolome in mild cases. Our results revealed that plasma lipids and alterations in their saturation level are important biomarkers for the detection of the infection. We also identified deoxy-fructosyl-amino acids as new putative plasma biomarkers for SARS-CoV-2 infection and COVID-19 severity. Finally, our results highlight a key role for plasma levels of tryptophan and kynurenine in the symptoms of COVID-19 patients.ConclusionOur results showed that plasma metabolome profiling is an efficient tool for the diagnosis and prognosis of SARS-CoV-2 infection.</p

Image_2_Low baseline IFN-γ response could predict hospitalization in COVID-19 patients.jpeg

The SARS-CoV-2 infection has spread rapidly around the world causing millions of deaths. Several treatments can reduce mortality and hospitalization. However, their efficacy depends on the choice of the molecule and the precise timing of its administration to ensure viral clearance and avoid a deleterious inflammatory response. Here, we investigated IFN-γ, assessed by a functional immunoassay, as a predictive biomarker for the risk of hospitalization at an early stage of infection or within one month prior to infection. Individuals with IFN-γ levels below 15 IU/mL were 6.57-times more likely to be hospitalized than those with higher values (p65 years, and no vaccination were independently associated with hospitalization. In addition, we found a significant inverse correlation between low IFN-γ response and high level of IL-6 in plasma (Spearman’s rho=-0.38, p=0.003). Early analysis of the IFN-γ response in a contact or recently infected subject with SARS-CoV-2 could predict hospitalization and thus help the clinician to choose the appropriate treatment avoiding severe forms of infection and hospitalization.</p