BACKGROUND: To identify the potent metabolic biomarkers and time of injury of traumatic brain injured (TBI). METHODS: A total of 70 Sprague-Dawley rats were used to establish the TBI model in this study. The serum was collected at 3 h, 6 h, 12 h, 24 h, 3 days and 7 days after surgery. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was performed to analyze metabolic changes in the serum of the TBI rats from different groups. The differences between the metabolic profiles of the rats in seven groups were analyzed using partial least squares discriminant analysis. RESULTS: Metabolic profiling revealed significant differences between the sham-operated and other groups. A total of 49 potential TBI metabolite biomarkers were identified between the sham-operated group and the model groups at different time points. Among them, six metabolites (methionine sulfone, kynurenine, 3-hydroxyanthranilic acid, 3-Indolepropionic acid, citric acid and glycocholic acid) were identified as biomarkers of TBI to estimate the injury time. CONCLUSION: Using metabolomic analysis, we identified new TBI serum biomarkers for accurate detection and determination of the timing of TBI injury.
BACKGROUND: To identify the potent metabolic biomarkers and time of injury of traumatic brain injured (TBI). METHODS: A total of 70 Sprague-Dawley rats were used to establish the TBI model in this study. The serum was collected at 3 h, 6 h, 12 h, 24 h, 3 days and 7 days after surgery. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was performed to analyze metabolic changes in the serum of the TBI rats from different groups. The differences between the metabolic profiles of the rats in seven groups were analyzed using partial least squares discriminant analysis. RESULTS: Metabolic profiling revealed significant differences between the sham-operated and other groups. A total of 49 potential TBI metabolite biomarkers were identified between the sham-operated group and the model groups at different time points. Among them, six metabolites (methionine sulfone, kynurenine, 3-hydroxyanthranilic acid, 3-Indolepropionic acid, citric acid and glycocholic acid) were identified as biomarkers of TBI to estimate the injury time. CONCLUSION: Using metabolomic analysis, we identified new TBI serum biomarkers for accurate detection and determination of the timing of TBI injury.