Poster De Conférence Année : 2021

Identification of Metabolic Biomarkers predictive of the severity of COVID-19 in hospitalized patients

V. Cunin
  • Fonction : Auteur

Résumé

In France, we are experiencing di erent waves of COVID-19, the importance of which is undermining our health care system. We try to identify as early as possible hospital- ized patients who are at risk of developing a severe form of COVID-19. The worsening of the disease is in part related to an acute respiratory distress syndrome related to immune system hyperactivation. It has been clearly demonstrated that co-morbidity factors related to dysmetabolic pathologies (diabetes, obesity, hypertension, etc.) are associated with se- vere forms. The pathophysiology of SARS-CoV2 infection has shown that this virus induces signi cant metabolic disturbances, probably related, at least in part, to the inactivation of angiotensin 2-converting enzyme, the gateway to the virus. Metabolomics has proven to be a reliable method for deep phenotyping and biomarker discovery. To date, it has been used primarily as a method to study metabolic perturbations induced by SARS-COV2 infection. This allows us to hypothesize that a metabolomics approach will lead to the discovery of metabolic biomarkers of aggravation. We have built a sample bank of more than 500 pa- tients hospitalized at Grenoble Alpes Hospital. We collected blood from patients within 3 days of hospitalization and stored the plasma within 4 hours. The teams of this consortium have brought together complementary and competent partners in the elds of infectiology, viral immunity, medical biochemistry or in the eld of metabolomics and biostatistics. This ambitious translational research project could provide new metabolic biomarker candidates of COVID-19 severity, allowing to stratify patients and anticipate intensive care bed man- agement.

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Dates et versions

hal-04959019 , version 1 (20-02-2025)

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  • HAL Id : hal-04959019 , version 1

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Audrey Le Gouellec, Sylvie Berthier, Candice Trocme, V. Cunin, Florence Castelli, et al.. Identification of Metabolic Biomarkers predictive of the severity of COVID-19 in hospitalized patients. 14èmes JS RFMF, Nov 2021, Aussois, France. ⟨hal-04959019⟩
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