Human Serum Metabolites Associate With Severity and Patient Outcomes in Traumatic Brain Injury.

Traumatic brain injury (TBI) is a major cause of death and disability worldwide, especially in children and young adults. TBI is an example of a medical condition where there are still major lacks in diagnostics and outcome prediction. Here we apply comprehensive metabolic profiling of serum samples from TBI patients and controls in two independent cohorts. The discovery study included 144 TBI patients, with the samples taken at the time of hospitalization. The patients were diagnosed as severe (sTBI; n=22), moderate (moTBI; n=14) or mild TBI (mTBI; n=108) according to Glasgow Coma Scale. The control group (n=28) comprised of acute orthopedic non-brain injuries. The validation study included sTBI (n=23), moTBI (n=7), mTBI (n=37) patients and controls (n=27). We show that two medium-chain fatty acids (decanoic and octanoic acids) and sugar derivatives including 2,3-bisphosphoglyceric acid are strongly associated with severity of TBI, and most of them are also detected at high concentrations in brain microdialysates of TBI patients. Based on metabolite concentrations from TBI patients at the time of hospitalization, an algorithm was developed that accurately predicted the patient outcomes (AUC=0.84 in validation cohort). Addition of the metabolites to the established clinical model (CRASH), comprising clinical and computed tomography data, significantly improved prediction of patient outcomes. The identified 'TBI metabotype' in serum, that may be indicative of disrupted blood-brain barrier, of protective physiological response and altered metabolism due to head trauma, offers a new avenue for the development of diagnostic and prognostic markers of broad spectrum of TBIs.European Union FP7 project TBIcare (Grant ID: 270259), GE-NFL Head Health Challenge I Award (Grant ID: 7620), EVO (Finland), Maire Taponen Foundation, National Institute for Health Research, National Institute for Health Research Biomedical Research Centre Cambridge (Neuroscience Theme; Brain Injury and Repair Theme)This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.ebiom.2016.07.01

Admission Levels of Total Tau and β-Amyloid Isoforms 1–40 and 1–42 in Predicting the Outcome of Mild Traumatic Brain Injury

Background: The purpose of this study was to investigate if admission levels of total tau (T-tau) and β-amyloid isoforms 1-40 (Aβ40) and 1-42 (Aβ42) could predict clinical outcome in patients with mild traumatic brain injury (mTBI). Methods: A total of 105 patients with mTBI [Glasgow Coma Scale (GCS) ≥ 13] recruited in Turku University Hospital, Turku, Finland were included in this study. Blood samples were drawn within 24 h of admission for analysis of plasma T-tau, Aβ40, and Aβ42. Patients were divided into computed tomography (CT)-positive and CT-negative groups. The outcome was assessed 6–12 months after the injury using the Extended Glasgow Outcome Scale (GOSE). Outcomes were defined as complete (GOSE 8) or incomplete (GOSE < 8) recovery. The Rivermead Post Concussion Symptoms Questionnaire (RPCSQ) was also used to assess mTBI-related symptoms. Predictive values of the biomarkers were analyzed independently, in panels and together with clinical parameters. Results: The admission levels of plasma T-tau, Aβ40, and Aβ42 were not significantly different between patients with complete and incomplete recovery. The levels of T-tau, Aβ40, and Aβ42 could poorly predict complete recovery, with areas under the receiver operating characteristic curve 0.56, 0.52, and 0.54, respectively. For the whole cohort, there was a significant negative correlation between the levels of T-tau and ordinal GOSE score (Spearman ρ = −0.231, p = 0.018). In a multivariate logistic regression model including age, GCS, duration of posttraumatic amnesia, Injury Severity Score (ISS), time from injury to sampling, and CT findings, none of the biomarkers could predict complete recovery independently or together with the other two biomarkers. Plasma levels of T-tau, Aβ40, and Aβ42 did not significantly differ between the outcome groups either within the CT-positive or CT-negative subgroups. Levels of Aβ40 and Aβ42 did not significantly correlate with outcome, but in the CT-positive subgroup, the levels of T-tau significantly correlated with ordinal GOSE score (Spearman ρ = −0.288, p = 0.035). The levels of T-tau, Aβ40, and Aβ42 were not correlated with the RPCSQ scores. Conclusions: The early levels of T-tau are correlated with the outcome in patients with mTBI, but none of the biomarkers either alone or in any combinations could predict complete recovery in patients with mTBI

Admission Levels of Total Tau and β-Amyloid Isoforms 1–40 and 1–42 in Predicting the Outcome of Mild Traumatic Brain Injury

Background: The purpose of this study was to investigate if admission levels of total tau (T-tau) and beta-amyloid isoforms 1-40 (A beta 40) and 1-42 (A beta 42) could predict clinical outcome in patients with mild traumatic brain injury (mTBI).Methods: A total of 105 patients with mTBI [Glasgow Coma Scale (GCS) >= 13] recruited in Turku University Hospital, Turku, Finland were included in this study. Blood samples were drawn within 24 h of admission for analysis of plasma T-tau, A beta 40, and A beta 42. Patients were divided into computed tomography (CT)-positive and CT-negative groups. The outcome was assessed 6-12 months after the injury using the Extended Glasgow Outcome Scale (GOSE). Outcomes were defined as complete (GOSE 8) or incomplete (GOSE Results: The admission levels of plasma T-tau, A beta 40, and A beta 42 were not significantly different between patients with complete and incomplete recovery. The levels of T-tau, A beta 40, and A beta 42 could poorly predict complete recovery, with areas under the receiver operating characteristic curve 0.56, 0.52, and 0.54, respectively. For the whole cohort, there was a significant negative correlation between the levels of T-tau and ordinal GOSE score (Spearman rho = -0.231, p = 0.018). In a multivariate logistic regression model including age, GCS, duration of posttraumatic amnesia, Injury Severity Score (ISS), time from injury to sampling, and CT findings, none of the biomarkers could predict complete recovery independently or together with the other two biomarkers. Plasma levels of T-tau, A beta 40, and A beta 42 did not significantly differ between the outcome groups either within the CT-positive or CT-negative subgroups. Levels of A beta 40 and A beta 42 did not significantly correlate with outcome, but in the CT-positive subgroup, the levels of T-tau significantly correlated with ordinal GOSE score (Spearman rho = -0.288, p = 0.035). The levels of T-tau, A beta 40, and A beta 42 were not correlated with the RPCSQ scores.Conclusions: The early levels of T-tau are correlated with the outcome in patients with mTBI, but none of the biomarkers either alone or in any combinations could predict complete recovery in patients with mTBI.</div

Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI

Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches

Cerebral Microbleeds and Structural White Matter Integrity in Patients With Traumatic Brain Injury-A Diffusion Tensor Imaging Study.

Diffuse axonal injury (DAI) is a common neuropathological manifestation of traumatic brain injury (TBI), presenting as traumatic alterations in the cerebral white matter (WM) microstructure and often leading to long-term neurocognitive impairment. These WM alterations can be assessed using diffusion tensor imaging (DTI). Cerebral microbleeds (CMBs) are a common finding on head imaging in TBI and are often considered a visible sign of DAI, although they represent diffuse vascular injury. It is poorly known how they associate with long-term white matter integrity. This study included 20 patients with TBI and CMBs, 34 patients with TBI without CMBs, and 11 controls with orthopedic injuries. DTI was used to assess microstructural WM alterations. CMBs were detected using susceptibility-weighted imaging (SWI) and graded according to their location in the WM and total lesion load was counted. Patients underwent SWI within 2 months after injury. DTI and clinical outcome assessment were performed at an average of eight months after injury. Outcome was assessed using the extended Glasgow Outcome Scale (GOSe). The Glasgow Coma Scale (GCS) and length of post-traumatic amnesia (PTA) were used to assess clinical severity of the injury. We found that CMB grading and total lesion load were negatively associated with fractional anisotropy (FA) and positively associated with mean diffusivity (MD). Patients with TBI and CMBs had decreased FA and increased MD compared with patients with TBI without CMBs. CMBs were also associated with worse clinical outcome. When adjusting for the clinical severity of the injury, none of the mentioned associations were found. Thus, the difference in FA and MD is explained by patients with TBI and CMBs having more severe injuries. Our results suggest that CMBs are not associated with greater WM alterations when adjusting for the clinical severity of TBI. Thus, CMBs and WM alterations may not be strongly associated pathologies in TBI

Admission Levels of Interleukin 10 and Amyloid β 1-40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury.

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1-40 (Aβ40) and 1-42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale-Extended 5-8, n = 49) and unfavorable (Glasgow Outcome Scale-Extended 1-4, n = 33) groups. The outcome was assessed 6-12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90-100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9-100) and specificity of 22.4% (95% CI: 10.2-32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1-4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7-6.2) with a sensitivity of 90.9% (95% CI: 81.8-100) and specificity of 59.2% (95% CI: 40.8-69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI

Glial fibrillary acidic protein and ubiquitin C-terminal hydrolase-L1 as outcome predictors in traumatic brain injury

OBJECTIVE: Biomarkers ubiquitin C-terminal hydrolase-L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) may help detect brain injury, assess its severity, and improve outcome prediction. This study aimed to evaluate the prognostic value of these biomarkers during the first days after brain injury. METHODS: Serum UCH-L1 and GFAP were measured in 324 patients with traumatic brain injury (TBI) enrolled in a prospective study. The outcome was assessed using the Glasgow Outcome Scale (GOS) or the extended version, Glasgow Outcome Scale-Extended (GOSE). RESULTS: Patients with full recovery had lower UCH-L1 concentrations on the second day and patients with favorable outcome had lower UCH-L1 concentrations during the first 2 days compared with patients with incomplete recovery and unfavorable outcome. Patients with full recovery and favorable outcome had significantly lower GFAP concentrations in the first 2 days than patients with incomplete recovery or unfavorable outcome. There was a strong negative correlation between outcome and UCH-L1 in the first 3 days and GFAP levels in the first 2 days. On arrival, both UCH-L1 and GFAP distinguished patients with GOS score 1-3 from patients with GOS score 4-5, but not patients with GOSE score 8 from patients with GOSE score 1-7. For UCH-L1 and GFAP to predict unfavorable outcome (GOS score ≤ 3), the area under the receiver operating characteristic curve was 0.727, and 0.723, respectively. Neither UCHL-1 nor GFAP was independently able to predict the outcome when age, worst Glasgow Coma Scale score, pupil reactivity, Injury Severity Score, and Marshall score were added into the multivariate logistic regression model. CONCLUSIONS: GFAP and UCH-L1 are significantly associated with outcome, but they do not add predictive power to commonly used prognostic variables in a population of patients with TBI of varying severities.This work was partially funded by the European Commission under the 7th Framework Programme (FP7-270259-TBIcare), the United Kingdom National Institute of Health Research Biomedical Research Centre at Cambridge, and a personal EVO grant (R.S.K.T.) from Hospital District of South-West Finland. V.F.N. is supported by a Health Foundation/Academy of Medical Sciences Clinician Scientist Fellowship. J.O., J.P.C., P.H., and D.K.M. were supported by the United Kingdom National Institute of Health Research Biomedical Research Centre at Cambridge, and D.K.M. was also supported by a Senior Investigator Award from the United Kingdom National Institute of Health Research

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

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.EU FP7 project TBIcare - Project ref. 270259 NIHR Cambridge Biomedical Research Centr