Brain protein biomarker clearance to blood in traumatic brain injury (TBI) is not fully understood. The aim of this study was to analyze the effect that a disrupted blood-brain barrier (BBB) had on biomarker clearance. Seventeen severe TBI patients admitted to Karolinska University Hospital were prospectively included. Cerebrospinal fluid (CSF) and blood concentrations of S100 calcium binding protein B (S100B) and neuron-specific enolase (NSE) were analyzed every 6-12 h for *1 week. Blood and CSF albumin were analyzed every 12-24 h, and BBB integrity was assessed using the CSF:blood albumin quotient (Q A ). We found that time-dependent changes in the CSF and blood levels of the two biomarkers were similar, but that the correlation between the biomarkers and Q A was lower for NSE (q = 0.444) than for S100B (q = 0.668). Because data were longitudinal, we also conducted cross correlation analyses, which indicated a directional flow and lagtime of biomarkers from CSF to blood. For S100B, this lag-time could be ascribed to BBB integrity, whereas for NSE it could not. Upon inferential modelling, using generalized least square estimation (S100B) or linear mixed models (NSE), Q A ( p = 0.045), time from trauma ( p < 0.001), time from trauma 2 ( p = 0.023), and CSF biomarker levels ( p = 0.008) were independent predictors of S100B in blood. In contrast, for NSE, only time from trauma was significant ( p < 0.001). These findings are novel and important, but must be carefully interpreted because of different characteristics between the two proteins. Nonetheless, we present the first data that indicate that S100B and NSE are cleared differently from the central nervous system, and that both the disrupted BBB and additional alternative pathways, such as the recently described glymphatic system, may play a role. This is of importance both for clinicians aiming to utilize these biomarkers and for the pathophysiological understanding of brain protein clearance, but warrants further examination.

Background: Despite seemingly functional coagulation, hemorrhagic lesion progression is a common and devastating condition following traumatic brain injury (TBI), stressing the need for new diagnostic techniques. Multiple electrode aggregometry (MEA) measures platelet function and could aid in coagulopathy assessment following TBI. The aims of this study were to evaluate MEA temporal dynamics, influence of concomitant therapy, and its capabilities to predict lesion progression and clinical outcome in a TBI cohort.Material and methods: Adult TBI patients in a neurointensive care unit that underwent MEA sampling were retrospectively included. MEA was sampled if the patient was treated with antiplatelet therapy, bled heavily during surgery, or had abnormal baseline coagulation values. We assessed platelet activation pathways involving the arachidonic acid receptor (ASPI), P2Y12 receptor, and thrombin receptor (TRAP). ASPI was the primary focus of analysis. If several samples were obtained, they were included. Retrospective data were extracted from hospital charts. Outcome variables were radiologic hemorrhagic progression and Glasgow Outcome Scale assessed prospectively at 12 months posttrauma. MEA levels were compared between patients on antiplatelet therapy. Linear mixed effect models and uni-/multivariable regression models were used to study longitudinal dynamics, hemorrhagic progression and outcome, respectively. results: In total, 178 patients were included (48% unfavorable outcome). ASPI levels increased from initially low values in a time-dependent fashion (p < 0.001). Patients on cyclooxygenase inhibitors demonstrated low ASPI levels (p < 0.001), while platelet transfusion increased them (p < 0.001). The first ASPI (p = 0.039) and TRAP (p = 0.009) were significant predictors of outcome, but not lesion progression, in univariate analyses. In multivariable analysis, MEA values were not independently correlated with outcome.

Background Severe traumatic brain injury (TBI) is associated with blood–brain barrier (BBB) disruption and a subsequent neuroinflammatory process. We aimed to perform a multiplex screening of brain enriched and inflammatory proteins in blood and cerebrospinal fluid (CSF) in order to study their role in BBB disruption, neuroinflammation and long-term functional outcome in TBI patients and healthy controls. Methods We conducted a prospective, observational study on 90 severe TBI patients and 15 control subjects. Clinical outcome data, Glasgow Outcome Score, was collected after 6–12 months. We utilized a suspension bead antibody array analyzed on a FlexMap 3D Luminex platform to characterize 177 unique proteins in matched CSF and serum samples. In addition, we assessed BBB disruption using the CSF-serum albumin quotient (QA), and performed Apolipoprotein E-genotyping as the latter has been linked to BBB function in the absence of trauma. We employed pathway-, cluster-, and proportional odds regression analyses. Key findings were validated in blood samples from an independent TBI cohort. Results TBI patients had an upregulation of structural CNS and neuroinflammatory pathways in both CSF and serum. In total, 114 proteins correlated with QA, among which the top-correlated proteins were complement proteins. A cluster analysis revealed protein levels to be strongly associated with BBB integrity, but not carriage of the Apolipoprotein E4-variant. Among cluster-derived proteins, innate immune pathways were upregulated. Forty unique proteins emanated as novel independent predictors of clinical outcome, that individually explained ~ 10% additional model variance. Among proteins significantly different between TBI patients with intact or disrupted BBB, complement C9 in CSF (p = 0.014, ΔR2 = 7.4%) and complement factor B in serum (p = 0.003, ΔR2 = 9.2%) were independent outcome predictors also following step-down modelling. Conclusions This represents the largest concomitant CSF and serum proteomic profiling study so far reported in TBI, providing substantial support to the notion that neuroinflammatory markers, including complement activation, predicts BBB disruption and long-term outcome. Individual proteins identified here could potentially serve to refine current biomarker modelling or represent novel treatment targets in severe TBI.

Background: Secondary transports of patients suffering from traumatic brain injury (TBI) may result in a delayed management and neurosurgical intervention, which is potentially detrimental. The aim of this study was to study the effect of triaging and delayed transfers on outcome, specifically studying time to diagnostics and neurosurgical management.Methods: This was a retrospective observational cohort study of TBI patients in need of neurosurgical care, 15 years and older, in the Stockholm Region, Sweden, from 2008 throughout 2014. Data were collected from pre-hospital and in-hospital charts. Known TBI outcome predictors, including the protein biomarker of brain injury S100B, were used to assess injury severity. Characteristics and outcomes of direct trauma center (TC) and those of secondary transfers were evaluated and compared. Functional outcome, using the Glasgow Outcome Scale, was assessed in survivors at 6–12 months after trauma. Regression models, including propensity score balanced models, were used for endpoint assessment.Results: A total of n = 457 TBI patients were included; n = 320 (70%) patients were direct TC transfers, whereas n = 137 (30%) were secondary referrals. In all, n = 295 required neurosurgery for the first 24 h after trauma (about 75% of each subgroup). Direct TC transfers were more severely injured (median Glasgow Coma Scale 8 vs. 13) and more often suffered a high energy trauma (31 vs. 2.9%) than secondary referrals. Admission S100B was higher in the TC transfer group, though S100B levels 12–36 h after trauma were similar between cohorts. Direct or indirect TC transfer could be predicted using propensity scoring. The secondary referrals had a shorter distance to the primary hospital, but had later radiology and surgery than the TC group (all p &lt; 0.001). In adjusted multivariable analyses with and without propensity matching, direct or secondary transfers were not found to be significantly related to outcome. Time from trauma to surgery did not affect outcome.Conclusions: TBI patients secondary transported to a TC had surgical intervention performed hours later, though this did not affect outcome, presumably demonstrating that accurate pre-hospital triaging was performed. This indicates that for selected patients, a wait-and-see approach with delayed neurosurgical intervention is not necessarily detrimental, but warrants further research.

Background Neuroinflammation following traumatic brain injury (TBI) has been shown to be associated with secondary injury development; however, how systemic inflammatory mediators affect this is not fully understood. The aim of this study was to see how systemic inflammation affects markers of neuroinflammation, if this inflammatory response had a temporal correlation between compartments and how different compartments differ in cytokine composition. Methods TBI patients recruited to a previous randomised controlled trial studying the effects of the drug anakinra (Kineret®), a human recombinant interleukin-1 receptor antagonist (rhIL1ra), were used (n = 10 treatment arm, n = 10 control arm). Cytokine concentrations were measured in arterial and jugular venous samples twice a day, as well as in microdialysis-extracted brain extracellular fluid (ECF) following pooling every 6 h. C-reactive protein level (CRP), white blood cell count (WBC), temperature and confirmed systemic clinical infection were used as systemic markers of inflammation. Principal component analyses, linear mixed-effect models, cross-correlations and multiple factor analyses were used. Results Jugular and arterial blood held similar cytokine information content, but brain-ECF was markedly different. No clear arterial to jugular gradient could be seen. No substantial delayed temporal associations between blood and brain compartments were detected. The development of a systemic clinical infection resulted in a significant decrease of IL1-ra, G-CSF, PDGF-ABBB, MIP-1b and RANTES (p < 0.05, respectively) in brain-ECF, even if adjusting for injury severity and demographic factors, while an increase in several cytokines could be seen in arterial blood. Conclusions Systemic inflammation, and infection in particular, alters cytokine levels with different patterns seen in brain and in blood. Cerebral inflammatory monitoring provides independent information from arterial and jugular samples, which both demonstrate similar information content. These findings could present potential new treatment options in severe TBI patients, but novel prospective trials are warranted to confirm these associations. Graphical abstract