Depuy-Synthes Award for Resident Research on Brain and Craniofacial Injury 155 Blood Metabolic Patterns Correlate With the Severity of Traumatic Brain Injury. Issue Volume 61:Issue CN Supp. 1(2014)Supplement (1st August 2014) - Posti, Jussi; Hyötyläinen, Tuulia; Jäntti, Sirkku; Ala-Seppälä, Henna; Coles, Jonathan; Katila, Ari; Kyllönen, Anna; Maanpää, Henna-Riikka; Menon, David K.; Outrim, Joanne; Hutchinson, Peter J.; Carpenter, Keri; et al.
Abstract: INTRODUCTION: Traumatic brain injury (TBI) has a substantial impact on brain metabolism. The purpose of this study was to identify blood metabolic biomarkers associated with TBI. METHODS: Our study population comprised of consecutive non-selected 256 adult patients with acute TBI and 36 patients with acute orthopedic trauma without acute or previous brain disorders who served as controls. The blood samples were taken at presentation, and then at 1, 2, 3 and 7 days after the injury whenever possible. Plasma samples were analyzed with comprehensive 2-dimensional gas chromatography coupled to time-of-flight mass spectrometry. A total of 851 metabolites were measured. Univariate and multivariate approaches were applied to investigate correlations between metabolic patterns and TBI severity, previously known clinical descriptors of TBI, and extracranial injury. In order to investigate the origin of the metabolites, metabolic patterns in brain microdialysates (BMD) were analyzed from selected TBI patients and the metabolites were searched from human cerebrospinal fluid (CSF) samples. In addition, the metabolic profiles were utilized for the prediction of the patient outcomes. RESULTS: Forty-three metabolites showed significant differences between the patients with TBI and controls. The differences between cases and controls were most prominent for patients with severe TBI. A statistical model comprising 2 serum metabolites was developed which predicted patient outcomes based on metabolomic data at the time of presentation. CONCLUSION: Serum metabolic profiles showed substantial differences between cases and controls, as well as between severe, moderate, and mild TBI. These results show that metabolic patterns could provide an objective means of estimating TBI severity, based on the host metabolic response to injury. In addition, the metabolic biomarkers found to be associated with a diagnosis of TBI were strongly associated with worse patient outcomes. The metabolic patterns observed were unique to TBI, and showed no strong correlations with extracranial injuries.