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J Neurotrauma. 2018 Nov 15;35(22):2673-2683. doi: 10.1089/neu.2017.5272. Epub 2018 Aug 21.

Serum Metabolites Associated with Computed Tomography Findings after Traumatic Brain Injury.

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1 Turku Centre for Biotechnology, University of Turku , Turku, Finland .
2 Turku Brain Injury Centre, Turku University Hospital , Turku, Finland .
3 Department of Neurology, University of Turku , Turku, Finland .
4 Division of Clinical Neurosciences, Department of Neurosurgery, Turku University Hospital , Turku, Finland .
5 Perioperative Services, Intensive Care Medicine and Pain Management, Turku University Hospital and University of Turku , Turku, Finland .
6 Steno Diabetes Center Copenhagen , Gentofte, Denmark .
7 Division of Anaesthesia, Department of Medicine, University of Cambridge , Addenbrooke's Hospital, Cambridge, United Kingdom .
8 Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge , Addenbrooke's Hospital, Cambridge, United Kingdom .
9 Department of Chemistry, Örebro University , Örebro, Sweden .
10 Schools of Medical Science, Örebro University , Örebro, Sweden .


There is a need to rapidly detect patients with traumatic brain injury (TBI) who require head computed tomography (CT). Given the energy crisis in the brain following TBI, we hypothesized that serum metabolomics would be a useful tool for developing a set of biomarkers to determine the need for CT and to distinguish among different types of injuries observed. Logistical regression models using metabolite data from the discovery cohort (n = 144, Turku, Finland) were used to distinguish between patients with traumatic intracranial findings and those with negative findings on head CT. The resultant models were then tested in the validation cohort (n = 66, Cambridge, United Kingdom). The levels of glial fibrillary acidic protein and ubiquitin C-terminal hydrolase-L1 were also quantified in the serum from the same patients. Despite there being significant differences in the protein biomarkers in patients with TBI, the model that determined the need for a CT scan validated poorly (area under the curve [AUC] = 0.64: Cambridge patients). However, using a combination of six metabolites (two amino acids, three sugar derivatives, and one ketoacid) it was possible to discriminate patients with intracranial abnormalities on CT and patients with a normal CT (AUC = 0.77 in Turku patients and AUC = 0.73 in Cambridge patients). Further, a combination of three metabolites could distinguish between diffuse brain injuries and mass lesions (AUC = 0.87 in Turku patients and AUC = 0.68 in Cambridge patients). This study identifies a set of validated serum polar metabolites, which associate with the need for a CT scan. Additionally, serum metabolites can also predict the nature of the brain injury. These metabolite markers may prevent unnecessary CT scans, thus reducing the cost of diagnostics and radiation load.


CT scanning; TBI; biomarkers; human studies; metabolism

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