Related Experiment Video
Updated: Nov 27, 2025

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
Published on: November 29, 2024
Metabolomics of exhaled breath in critically ill COVID-19 patients: A pilot study
Stanislas Grassin-Delyle1, Camille Roquencourt2, Pierre Moine3
1Hôpital Foch, Exhalomics®, Département des maladies des voies respiratoires, Suresnes, France (S.G.D., H.S., E.N., L-J.C., P.D.); Université Paris-Saclay, UVSQ, INSERM, Infection et inflammation, Montigny le Bretonneux, France (S.G.D., P.M., N.H., D.A.); FHU SEPSIS (Saclay and Paris Seine Nord Endeavour to PerSonalize Interventions for Sepsis) (S.G.D., H.S., E.N., L-J.C., P.D., E.T., D.A.)..
Background:
Early diagnosis of coronavirus disease 2019 (COVID-19) is of the utmost importance but remains challenging. The objective of the current study was to characterize exhaled breath from mechanically ventilated adults with COVID-19.
Methods:
In this prospective observational study, we used real-time, online, proton transfer reaction time-of-flight mass spectrometry to perform a metabolomic analysis of expired air from adults undergoing invasive mechanical ventilation in the intensive care unit due to severe COVID-19 or non-COVID-19 acute respiratory distress syndrome (ARDS).
Findings:
Between March 25th and June 25th, 2020, we included 40 patients with ARDS, of whom 28 had proven COVID-19. In a multivariate analysis, we identified a characteristic breathprint for COVID-19. We could differentiate between COVID-19 and non-COVID-19 ARDS with accuracy of 93% (sensitivity: 90%, specificity: 94%, area under the receiver operating characteristic curve: 0·94-0·98, after cross-validation). The four most prominent volatile compounds in COVID-19 patients were methylpent-2-enal, 2,4-octadiene 1-chloroheptane, and nonanal.
Interpretation:
The real-time, non-invasive detection of methylpent-2-enal, 2,4-octadiene 1-chloroheptane, and nonanal in exhaled breath may identify ARDS patients with COVID-19.
Funding:
The study was funded by Agence Nationale de la Recherche (SoftwAiR, ANR-18-CE45-0017 and RHU4 RECORDS, Programme d'Investissements d'Avenir, ANR-18-RHUS-0004), Région Île de France (SESAME 2016), and Fondation Foch.
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