Back to Search Start Over

Nuclear magnetic resonance-based serum metabolomic analysis reveals different disease evolution profiles between septic shock survivors and non-survivors

Authors :
Philippe Savarin
Nadia Bouchemal
Roland Amathieu
Zhicheng Liu
Mohamed N. Triba
Laurence Le Moyec
Xiangping Lin
Edith Hantz
Chimie, Structures et Propriétés de Biomatériaux et d'Agents Thérapeutiques (CSPBAT)
Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Paris 13 (UP13)-Institut Galilée-Université Sorbonne Paris Cité (USPC)
Service d'Anesthésie et des Réanimations Chirurgicales
Centre Hospitalier Universitaire Henri Mondor-Université Paris Est Créteil Val de Marne (Paris 12) (UPEC)
Unité de biologie intégrative des adaptations à l'exercice (UBIAE)
Université d'Évry-Val-d'Essonne (UEVE)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Université Paris 13 (UP13)-Institut Galilée-Université Sorbonne Paris Cité (USPC)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)
Savarin, Philippe
Source :
Critical Care, Critical Care, BioMed Central, 2019, 23 (1), ⟨10.1186/s13054-019-2456-z⟩, Critical Care, 2019, 23 (1), ⟨10.1186/s13054-019-2456-z⟩, Critical Care, Vol 23, Iss 1, Pp 1-12 (2019)
Publication Year :
2019
Publisher :
HAL CCSD, 2019.

Abstract

Background Septic shock is the most severe phase of sepsis and is associated with high rates of mortality. However, early stage prediction of septic shock outcomes remains difficult. Metabolomic techniques have emerged as a promising tool for improving prognosis. Methods Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) models separating the serum metabolomes of survivors from those of non-survivors were established with samples obtained at the intensive care unit (ICU) admission (H0) and 24 h later (H24). For 51 patients with available H0 and H24 samples, multi-level modeling was performed to provide insight into different metabolic evolutions that occurred between H0 and H24 in the surviving and non-surviving patients. Relative quantification and receiver operational characteristic curves (ROC) were applied to estimate the predictability of key discriminatory metabolites for septic shock mortality. Results Metabolites that were involved in energy supply and protein breakdown were primarily responsible for differentiating survivors from non-survivors. This was not only seen in the H0 and H24 discriminatory models, but also in the H0-H24 paired models. Reanalysis of extra H0-H24 paired samples in the established multi-level model demonstrated good performance of the model for the classification of samplings. According to the ROC results, nine discriminatory metabolites defined consistently from the unpaired model and the H0-H24 time-trend change (ΔH24-H0) show good prediction of mortality. These results suggest that NMR-based metabolomic analysis is useful for a better overall assessment of septic shock patients. Conclusions Dysregulation of the metabolites identified by this study is associated with poor outcomes for septic shock. Evaluation of these compounds during the first 24 h after ICU admission in the septic shock patient may be helpful for estimating the severity of cases and for predicting outcomes. Trial registration All human serum samples were collected and stored, provided by the “center of biologic resources for liver disease”, in Jean Verdier Hospital, Bondy, France (BB-0033-00027). Electronic supplementary material The online version of this article (10.1186/s13054-019-2456-z) contains supplementary material, which is available to authorized users.

Details

Language :
English
ISSN :
13648535 and 1466609X
Database :
OpenAIRE
Journal :
Critical Care, Critical Care, BioMed Central, 2019, 23 (1), ⟨10.1186/s13054-019-2456-z⟩, Critical Care, 2019, 23 (1), ⟨10.1186/s13054-019-2456-z⟩, Critical Care, Vol 23, Iss 1, Pp 1-12 (2019)
Accession number :
edsair.doi.dedup.....a02ea3bb725e3fb76ca163fdaa1e07a4
Full Text :
https://doi.org/10.1186/s13054-019-2456-z⟩