[Nuclear magnetic resonance based metabolic phenotyping for patient evaluations in operating rooms and intensive care units]

Ann Fr Anesth Reanim. 2014 Mar;33(3):167-75. doi: 10.1016/j.annfar.2013.12.005. Epub 2014 Jan 20.
[Article in French]

Abstract

Metabolic phenotyping consists in the identification of subtle and coordinated metabolic variations associated with various pathophysiological stimuli. Different analytical methods, such as nuclear magnetic resonance, allow the simultaneous quantification of a large number of metabolites. Statistical analyses of these spectra thus lead to the discrimination between samples and the identification of a metabolic phenotype corresponding to the effect under study. This approach allows the extraction of candidate biomarkers and the recovery of perturbed metabolic networks, driving to the generation of biochemical hypotheses (pathophysiological mechanisms, diagnostic tests, therapeutic targets…). Metabolic phenotyping could be useful in anaesthesiology and intensive care medicine for the evaluation, monitoring or diagnosis of life-threatening situations, to optimise patient managements. This review introduces the physical and statistical fundamentals of NMR-based metabolic phenotyping, describes the work already achieved by this approach in anaesthesiology and intensive care medicine. Finally, potential areas of interest are discussed for the perioperative and intensive management of patients, from newborns to adults.

Keywords: Anaesthesiology; Anesthésie; Biomarkers; Biomarqueurs; Intensive care medicine; Metabolic network; Metabolic phenotyping; Nuclear magnetic resonance; Phénotypage métabolique; Réanimation; Réseau métabolique; Résonance magnétique nucléaire.

Publication types

  • English Abstract
  • Review

MeSH terms

  • Biomarkers / analysis
  • Critical Care / methods*
  • Humans
  • Magnetic Resonance Spectroscopy / methods*
  • Metabolic Diseases / diagnosis
  • Metabolism / physiology*
  • Monitoring, Intraoperative / methods*
  • Phenotype

Substances

  • Biomarkers