Metabolomics classifies phase of care and identifies risk for mortality in a porcine model of multiple injuries and hemorrhagic shock.

Background: Early recognition and intervention in hemorrhagic shock is essential to improved outcomes. However, the lack of robust diagnostic tools readily available to identify patients in the field inhibits the ability to provide timely intervention. Therefore, the development of a reliable prognostic indicator, such as a serum biomarker or a metabolic profile, has significant potential to improve far-forward trauma care. In this study, we used metabolomics as a tool to identify a metabolic state associated with the hemorrhagic shock and outcome in our porcine model of multiple injuries, shock, and resuscitation.

Methods: Proton nuclear magnetic resonance spectroscopy was used to evaluate serum metabolites from 23 animals that underwent multiple injuries, controlled hemorrhage, and 20 hours of a standard resuscitation protocol. Serum samples were collected from the animals at baseline (before hemorrhage), at shock (after 45 minutes of shock), and at 8 hours of full resuscitation.

Results: We were able to demonstrate shifts in the metabolome throughout different time points and construct a metabolic profile associated with mortality using partial least squares discriminate analysis. The metabolites most responsible for the classification of hemorrhagic shock in our model serve as markers for ischemia, changes in energy production, and cellular damage. Hemorrhagic shock was characterized by marked increases in tricarboxylic acid cycle intermediates, glycolytic-gluconeogenic by-products, purine-pyrimidine catabolism, and fatty acid oxidation.

Conclusion: The results of this study demonstrate the potential for metabolomics as a tool to classify the metabolic flux, to identify relevant biochemical pathways, and to identify clinically useful biomarkers.