Purpose: Endotheliopathy of trauma (EoT), as defined by circulating levels of syndecan-1 ≥ 40 ng/mL, has been reported to be associated with significantly increased transfusion requirements and a doubled 30-day mortality. Increased shedding of the glycocalyx points toward the endothelial cell membrane composition as important for the clinical outcome being the rationale for this study.
Results: The plasma metabolome of 95 severely injured trauma patients was investigated by mass spectrometry, and patients with EoT vs. non-EoT were compared by partial least square-discriminant analysis, identifying succinic acid as the top metabolite to differentiate EoT and non-EoT patients (VIP score = 3). EoT and non-EoT patients’ metabolic flux profile was inferred by integrating the corresponding plasma metabolome data into a genome-scale metabolic network reconstruction analysis and performing a functional study of the metabolic capabilities of each group. Model predictions showed a decrease in cholesterol metabolism secondary to impaired mevalonate synthesis in EoT compared to non-EoT patients. Intracellular task analysis indicated decreased synthesis of thromboxanA2 and leukotrienes, as well as a lower carnitine palmitoyltransferase I activity in EoT compared to non-EoT patients. Sensitivity analysis also showed a significantly high dependence of eicosanoid-associated metabolic tasks on alpha-linolenic acid as unique to EoT patients.
Conclusions: Model-driven analysis of the endothelial cells’ metabolism identified potential novel targets as impaired thromboxane A2 and leukotriene synthesis in EoT patients when compared to non-EoT patients. Reduced thromboxane A2 and leukotriene availability in the microvasculature impairs vasoconstriction ability and may thus contribute to shock in EoT patients. These findings are supported by extensive scientific literature; however, further investigations are required on these findings.
|Journal||Matrix Biology Plus|
|Number of pages||16|
|Publication status||Published - 2022|
- Genome-scale metabolic model
- Systems biology