Metabolic alterations associated with hemorrhagic shock and traumatic injury as measured in the urine.

Abstract

Introduction: This dissertation focuses on profiling the changes in metabolism that occur as a result of hemorrhagic shock and traumatic injury as observed in urine obtained from a porcine model. Hemorrhagic shock and traumatic injury are responsible for the majority of deaths under the age of 44. A porcine model of hemorrhagic shock and traumatic injury was used to examine changes in metabolism due to hemorrhagic shock and traumatic injury. Changes in metabolism were hypothesized to be dependent upon the metabolic state the animal occupies upon injury (fed or fasted). It was also hypothesized that a metabolite or metabolites could serve as a marker of mortality. Materials and Methods: Nuclear magnetic resonance (NMR) spectroscopy and Chenomx software were used to generate individual profiles of metabolite concentrations (the metabolome) for each urine sample obtained. Because hemorrhagic shock produces drastic changes in urine concentration and large fluctuations in the concentrations of endogenous metabolites in the urine, urine must be normalized to urine output to allow for accurate comparisons between urine samples. The urinary metabolome was analyzed with partial least squares discriminant analysis (PLS-DA) and with a scale-free network. Results: PLS-DA models showed that metabolites associated with respiration, ischemia/reperfusion injury, and cell membrane damage were observed in the urine two hours after the initiation of resuscitation. Other metabolites which may be associated with injury sustained from surgical preparation were observed at 20 hours after the initiation of resuscitation. The metabolites 1,6-Anhydro β-D-glucose and mannose were associated with the metabolome of fed animals. The network analysis of the metabolome is reflective of the scale-invariant nature of metabolism. Respiratory metabolites were separated by whether they are involved in aerobic or anaerobic respiration. Anaerobic metabolites were also associated with markers of cell membrane rupture. Lactate, pyruvate, 2-oxoglutarate, succinate, taurine, glycine, dimethylamine, and creatinine were identified as well-connected hub metabolites in the network. No metabolites were associated with survival alone. Conclusions: The pathophysiology associated with hemorrhagic shock can be treated as a scale invariant process particularly with respect to metabolism. Results from a traditional metabolomics treatment of the data with PLS-DA models were congruent with results from a scale-invariant, weakly modular network of the urinary metabolome. Other samples obtained from these experiments (muscle, liver, and serum) could benefit from a similar treatment. Additional work in (a) integrating the metabolomes of all four biological samples and (b) creating a physics-based theory of hemorrhagic shock may provide important information about mortality and the propagation of injury.