Serum brain-enriched biomarkers are increasingly employed in the clinical evaluation of traumatic brain injury (TBI) to assist with triage, neuroimaging decisions, and prognostication. However, the potential of temporal biomarker trajectories to inform disease monitoring and long-term outcomes remains underexplored. We aim to identify distinct biomarker trajectory (TRAJ) profiles in traumatic brain injury patients and to examine their associations with long-term clinical outcomes. The study included 373, CT-positive Intensive Care Unit (ICU) traumatic brain injury patients (256 with initial Glasgow Coma Scale 3-12) from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) core study who had at least two serum samples collected between days 1 and 5 post-injury. Six biomarkers -glial fibrillary acidic protein, ubiquitin C-terminal hydrolase-L1, neurofilament light chain, Tau, S100B, and neuron-specific enolase- were analysed. Optimal cluster solutions were determined using a composite validation index derived from seven internal clustering metrics. Distinct high and low trajectory classes emerged for all biomarkers; each comprising at least 40% of the cohort for five of the biomarkers. Cross-biomarker concordance analysis identified composite high (n = 104) and low (n = 110) TRAJ profiles. Key metrics for evaluating patient outcomes include Glasgow Outcome Scale Extended (GOSE), mortality, and Quality of Life after Brain Injury Overall Scale (QoLIBRI-OS) at 3, 6, and 12 months as well as a prognostic incremental value analysis using a conventional prediction model: International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT). High TRAJ membership is strongly associated with poor functional recovery (GOSE 1-4 at 3-12 months; odds ratio (OR) 8.79 [95% confidence interval (CI): 4.56-16.97]-12.29 [95%CI: 6.19-24.40], P < 0.001) and increased 180-day mortality (OR (14.84 [95%CI: 5.56-39.64], P < 0.001). Conversely, low TRAJ membership predicted favourable recovery (GOSE 6-8 at 3-12 months; OR 7.42 [95%CI: 3.10-17.76]-10.83 [95%CI: 3.65-32.14], P < 0.001) and better quality of life (QoLIBRI-OS ≥52; OR 4.98 [95%CI: 1.92-12.89], P < 0.01). Compared to single day-1 biomarker measurements, trajectory-based profiles yielded larger effect sizes and provided incremental prognostic value when added to the IMPACT prediction model (ΔR² 9-17%, P < 0.05). Overall, repeated biomarker measurements across the acute phase yield superior prognostic accuracy relative to single timepoint assessments. These findings underscore the importance of integrating longitudinal biomarker monitoring into ICU-based traumatic brain injury care and suggest that temporal trajectory profiling may improve prognostic modelling and facilitate more precise patient stratification for both clinical management and interventional studies.

Intracranial hypertension (IH) is a major cause of secondary brain injury after traumatic brain injury (TBI) and is typically treated after onset. Machine learning (ML) approaches show promise for IH prediction, but methodological heterogeneity across studies limits comparability and clinical translation. We evaluated how key methodological choices influence ML performance for IH prediction. In this retrospective observational study, intracranial pressure (ICP), arterial blood pressure (ABP), and additional variables were collected from TBI patients in two Dutch hospitals and the CENTER-TBI high-resolution cohort. Six methodological categories were varied: IH definition (ICP ≥ 22 or ≥ 30 mmHg), input data configuration, labelling strategy (IH onset versus continuous labelling), temporal separation of control segments, observation window length (10–600 min), and model class (eXtreme Gradient Boosting, random forest, logistic regression, Gaussian naïve Bayes, and long short-term memory). Models were evaluated using patient-level tenfold cross-validation with area under the receiver operating characteristic curve (AUC) as primary outcome. We included 316 patients. Prediction performance varied substantially across methodological choices. Continuous labelling inflated performance, and optimal observation windows were 240–360 min. Across conditions, eXtreme Gradient Boosting achieved the highest performance (AUC 0.92). These findings highlight the need for standardized methodology and transparent reporting in IH prediction studies.

Background: Traumatic brain injury (TBI) frequently leads to long-term neurological deficits. Recent research also implicates cellular senescence—a state of permanent cell cycle arrest driven by DNA damage—as a key contributor to neuroinflammation and cognitive decline. This study investigates the cell-type specificity of senescence within glial and vascular cells of the neurovascular unit (NVU) following experimental TBI in a rat model. Methods: Rats underwent various TBI scenarios, including single severe TBI (sTBI), single mild TBI (mTBI), repetitive mild TBI (rmTBI) and repetitive sham-operated control (rSham). Twenty-four hours or four weeks later, brains were harvested and brain sections were co-stained for γH2AX and cell type-specific markers. Immunofluorescence microscopy was used to comprehensively assess senescence in both glial and vascular cells of the NVU, specifically astrocytes, microglia, endothelial cells, and pericytes. Results: We observed acute increased astrocyte senescence in sTBI samples and microglial senescence in mTBI and sTBI samples in the neocortex, while endothelial cell senescence was significantly elevated in the neocortex of the sTBI group after four weeks. Pericytes did not exhibit significant signs of senescence at either time point. Conclusion: These findings demonstrate differential γH2AX labelling of NVU components following TBI, suggesting that vulnerability to TBI-induced senescence can be specific both to the cell type and the time after the injury. This has implications on therapies targeting senescent cells for mitigating the long-term consequences of TBI.

BACKGROUND:Post-cardiac arrest brain injury is driven by both global cerebral hypoperfusion and subsequent reperfusion. However, hyperacute blood-based neurobiomarker kinetics after precisely defined (very) low-flow intervals remain poorly characterized. During transcatheter aortic valve implantation (TAVI), rapid ventricular pacing (RVP) induces a transient pulseless ventricular tachycardia, functionally mimicking brief cardiac arrest. METHODS:In this single-center, prospective, self-controlled cohort study, adults undergoing TAVI were enrolled. RVP (120-200 bpm) was applied to transiently suppress forward flow. Invasive aortic pressure, common carotid (CCA) and middle cerebral artery (MCA) flow were recorded continuously. Serum samples were obtained pre-procedure and 20, 65, 110 and 200 min after RVP. Neuron specific enolase (NSE), and S100 were measured as neurobiomarkers. RESULTS:In case of the 76 enrolled patients, median cumulative RVP duration was 60 s (IQR 41-92). During RVP, MCA and CCA flow showed a very low-flow state while aortic pressure fell below the presumed autoregulatory threshold. NSE concentrations increased progressively from baseline to 200 min (T0: 10.6 [9.1-13.0]; T20: 12.8 [11.6-15.5]; T65: 15.1 [13.0-18.6]; T110: 15.8 [13.8-18.6]; T200: 17.0 [14.2-20.5] µg/L). S100B concentrations showed an inverse U-shaped profile (T0: 0.05 [0.04-0.07]; T20: 0.13 [0.10-0.18]; T65: 0.14 [0.11-0.23]; T110: 0.11 [0.08-0.16]; T200: 0.08 [0.06-0.12] µg/L). No patient developed neurological deficits. CONCLUSIONS:Controlled (very) low-flow episodes during TAVI induce measurable, but clinically silent, elevations of NSE and S100. Neurobiomarkers reflects with distinct kinetics on ischaemia and reperfusion following a short, very low-flow cardiac arrest.

Circulating biomarkers might improve the prediction of outcomes in patients with traumatic brain injury (TBI) beyond current approaches. Robust and up-to-date evidence is required to support their clinical utility and integration into medical practice to guide decision-making. Our objective was to critically appraise the existing evidence for six core blood-based TBI biomarkers (S100 calcium-binding protein B, glial fibrillary acidic protein [GFAP], neuron-specific enolase, ubiquitin C-terminal hydrolase-L1 [UCH-L1], tau and neurofilament proteins), in predicting outcome after TBI. Electronic databases, including Medline and Embase, were searched for articles published from their inception to October 2023. Studies were included if they evaluated the accuracy of blood biomarker concentrations at hospital presentation for outcome prediction in adult patients with TBI. Outcomes assessed were mortality, Glasgow Outcome Scale (GOS)/GOS extended (GOS-E), or the Rivermead Post-Concussion Symptoms Questionnaire (RPQ). Study selection, data extraction, and quality assessment using the modified Quality Assessment of Prognostic Accuracy Studies tool were performed by two authors independently, with disagreements being resolved through discussion or arbitration. If appropriate, a meta-analysis was conducted by calculating the weighted summary area under the curve (AUC) and using a bivariate regression model. Of 12,792 retrieved records, 32 articles, including 7481 patients with TBI, were selected as relevant. Two biomarkers showed strong associations with in-hospital and 6-month mortality: GFAP (unadjusted pooled AUC 0.81 [95% confidence interval [CI] 0.75-0.87] and 0.82 [0.80-0.85], respectively) and UCH-L1 (0.80 [0.74-0.85] and 0.83 [0.77-0.88]). Their addition to models that included established risk factors consistently improved the predictive value, though models and performance varied substantially across studies. In four studies measuring both markers, UCH-L1 outperformed GFAP in improving risk stratification when added to established prediction models. At ∼1.5 ng/mL (five studies), the summary sensitivity of GFAP for predicting mortality was 78% (95% CI 67-85%), and the summary specificity was 79% (95% CI 64-89%). The other assessed biomarkers had fair to good performance in mortality prediction with unclear added benefits. Neurofilament light (NfL) (three studies) demonstrated the strongest association in predicting a 6-month poor outcome (GOS-E ≤4; GOS ≤3) (unadjusted pooled AUC 0.81 [95% CI 0.75-0.87]), whereas the other assessed biomarkers had a fair performance with unclear or irrelevant added value. All core biomarkers had only marginal or no association with incomplete recovery and post-concussion symptoms/syndrome, as assessed by RPQ. Serious problems were found in the design and analysis of many of the studies. We conclude that admission measurements of core blood TBI biomarkers, in particular GFAP and UCH-L1, are strongly associated with mortality. There remains little evidence that any of these markers are ready for clinical implementation for prognostic purposes. Future work focused on the intended use and applying unbiased rigorous analysis methods is necessary to demonstrate that the biomarker test results are "prognostically actionable."

Severe traumatic brain injury (TBI) leads to chronic cognitive decline, imposing a significant societal burden. The regulation of cerebral blood flow (CBF) is critical for cognitive function, and acute disruptions in CBF regulation predict poor TBI outcomes. However, the long-term effects of TBI on CBF regulation and their association with cognitive function remain poorly understood. This study aimed to investigate whether severe TBI results in chronic CBF dysregulation and whether this contributes to long-term cognitive deficits. Additionally, we examined the role of TBI-induced insulin-like growth factor 1 (IGF-1) deficiency in cerebrovascular dysfunction. We assessed cognitive function, basal CBF (via phase contrast MRI), CBF autoregulation (via transcranial Doppler), and neurovascular coupling (NVC) in 33 TBI survivors (mean age 37.6 years, 10 years post-injury) and 21 age-matched healthy controls. Serum IGF-1 levels were also measured. TBI survivors exhibited significant impairments in memory and executive function compared to controls. While basal CBF and autoregulation remained intact, NVC responses were chronically impaired and correlated with cognitive deficits. However, IGF-1 levels did not differ between groups and were not associated with NVC impairment or cognitive function. Our findings indicate that severe TBI results in chronic impairment of neurovascular coupling, which likely contributes to long-term cognitive deficits. These results highlight the need for further research to identify underlying neurovascular mechanisms and develop interventions to restore NVC and cognitive function in TBI survivors.

This article explores the diagnostic performance of a panel of six biomarkers (glial fibrillary acidic protein [GFAP], neurofilament light [NFL], neuron-specific enolase [NSE], S100 calcium-binding protein B [S100B], total tau [t-tau], and ubiquitin C-terminal hydrolase L1 [UCH-L1]) in the context of the "2023 UK National Institute for Health and Care Excellence (NICE) Head Injury: Assessment and early management (NG232)" guideline. Emphasis is placed on subjects where clinical equipoise remains concerning the decision for head computed tomography (CT), medium-risk subjects. All adult subjects from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) dataset with a complete biomarker profile and interpretable CT scan within 24 h of injury were classified as high, medium, and low-risk according to the NICE NG232 Clinical Decision Rule (CDR) for CT head imaging following head injury. In subjects classified as medium-risk, the area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of biomarkers to identify those with (1) CT abnormality or (2) potential neurosurgical lesion, with CT considered the gold standard diagnosis. A time-to-biomarker sub-analysis was performed in subjects with a time from injury to sampling within 6 h, in keeping with current clinical usage of biomarkers. Among 1979 CENTER-TBI participants with sufficient clinical information to facilitate classification, 385 subjects were classified as medium-risk. Biomarker concentrations were significantly higher in those with traumatic CT abnormalities as compared with those without for all biomarkers aside from NSE (all p < 0.05). When sampled within 24 h of injury, GFAP demonstrated the best diagnostic performance for CT abnormality (AUC 0.81 [0.77-0.86]), with NFL, t-tau, and UCH-L1 showing moderate performance. At a threshold to provide a 95% sensitivity, GFAP, NFL, t-tau, and UCH-L1 demonstrated specificities ranging from 18% to 33% corresponding to a potential reduction of total CT images performed in these subjects by 14-23%. S100B and UCH-L1 showed improved performance when biomarker sampling time was limited to 6 h following injury. In intoxicated subjects with a persistent Glasgow Coma Score of 13-14, biomarker levels were significantly higher in subjects with CT abnormality as compared with those without. In conclusion, serum biomarkers demonstrate potential for the reduction in CT scan requirements in those classified as medium-risk in reference to the NG232 CDR criteria. These results highlight a need for further prospective studies on the use of diagnostic TBI biomarkers in current emergency medicine practice, with future consideration given to the integration of biomarkers in the NICE NG232 head injury guidelines.

Background and Objectives There is seemingly contradictory evidence concerning relationships between day-of-injury biomarkers and outcomes after mild traumatic brain injury (mTBI). To address this issue, we examined the association between a panel of biomarkers and multidimensional TBI outcomes. Methods Participants with mTBI (Glasgow coma scores [GCSs] 13-15) were selected from Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury, a European observational study recruiting patients with TBI with indication for brain CT and presentation within 24 hours. Exclusion criteria for this secondary analysis were age younger than 16 years, incomplete biomarker panel, death, or no recorded outcomes. Participants were separated into 2 groups, CT-negative and CT-positive. Multivariable binary logistic regression was used to assess the relation between the log biomarker level (glial fibrillary acidic protein [GFAP], neurofilament light [NfL], neuron-specific enolase [NSE], S100 calcium-binding protein B [S100B], tau, ubiquitin C-terminal hydrolase L1 [UCH-L1]) and dichotomized 6-month outcomes (functional outcomes [GOSE score <8], health-related quality of life [HRQoL; Quality of Life after Brain Injury-Overall Scale (QOLIBRI-OS) score <52, Short-Form 12-Item Survey version 2 Mental Component Summary (SF12v2 MCS) score <40, Short-Form 12-Item Survey version 2 Physical Component Summary (SF12v2 PCS) score <40], persistent postconcussion symptoms [Rivermead Post-Concussion Symptoms Questionnaire score >= 16], anxiety disorder [Generalized Anxiety Disorder-7 (GAD-7) score >= 8], depression [Patient Health Questionnaire-9 (PHQ-9) score >= 10], and post-traumatic stress disorder [PTSD Checklist for DSM-5 (PCL-5) score >= 33]). Results A total of 1,589 participants (865 CT-negative, 724 CT-positive) were included (77% GCS 15, median age 52 years, 66% male). Higher biomarker levels were associated with a GOSE score <8: CT-negative: S100B (odds ratio [OR] 1.78, 95% CI 1.43-2.23) and UCH-L1 (OR 1.16, 95% CI 1.01-1.33); CT-positive: GFAP (OR 1.22, 95% CI 1.11-1.36), NfL (OR 1.30, 95% CI 1.11-1.52), S100B (OR 1.51, 95% CI 1.23-1.86), tau (OR 1.36, 95% CI 1.17-1.59), and UCH-L1 (OR 1.34, 95% CI 1.17-1.53). In CT-positive participants, positive association was seen between NfL (OR 1.3, 95% CI 1.06-1.60) and UCH-L1 (OR 1.28, 95% CI 1.07-1.54) with QOLIBRI-OS; S100B (OR 1.32, 95% CI 1.02-1.70) with SF12v2 PCS; and NSE (OR 1.52, 95% CI 1.06-2.18) and UCH-L1 (OR 1.21, 95% CI 1.01-1.46) with the GAD-7. However, in CT-negative participants only, negative associations were seen between GFAP and impairment on the QOLIBRI-OS (OR 0.76, 95% CI 0.66-0.88), SF12v2 MCS (OR 0.71, 95% CI 0.61-0.82), SF12v2 PCS (OR 0.79, 95% CI 0.68-0.91), GAD-7 (OR 0.80, 0.68-0.95), PHQ-9 (OR 0.80, 95% CI 0.68-0.93), and PCL-5 (OR 0.80, 95% CI 0.66-0.97). Discussion Participants with higher biomarker levels had greater odds of impaired functional recovery. However, in CT-negative participants, higher GFAP concentrations were associated with better HRQoL and less impaired mental health. Further exploration is required of the patient phenotypes that may explain the relationships observed in this analysis.

Background Even patients with normal computed tomography (CT) head imaging may experience persistent symptoms for months to years after mild traumatic brain injury (mTBI). There is currently no good way to predict recovery and triage patients who may benefit fi t from early follow-up and targeted intervention. We aimed to assess if existing prognostic models can be improved by serum biomarkers or diffusion tensor imaging metrics (DTI) from MRI, and if serum biomarkers can identify patients for DTI. Methods We included 1025 patients aged >18 years with a Glasgow Coma Score >12 and normal CT from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study which recruited between December 19,2014 and December 17, 2017 (NCT02210221). Biomarkers (GFAP, NFL, S100B) were obtained at a median of 8.8 h (Q1-Q3 - Q3 4.2-16.7) - 16.7) and DTI at 13 days (3-19) - 19) after injury. DTI metrics were available in 153 patients for 48 white matter tracts (ICBM-DTI-81 atlas). Incomplete recovery at three months was defined fi ned as an extended Glasgow Outcome Scale score <8. Existing prognostic models were fi tted with and without biomarkers, or with and without DTI, and internally validated using bootstrapping. Findings 385 (38%) patients had incomplete recovery. Adding biomarkers did not improve performance beyond the best existing clinical prognostic model [optimism-corrected AUC 0.69 (95% CI 0.65-0.72) - 0.72) and R2 2 17% (11-22)]. - 22)]. Adding DTI metrics significantly fi cantly enhanced all models [best optimism-corrected AUC 0.82 (0.79-0.85) - 0.85) and R2 2 75% (39-100)]. - 100)]. The top three prognostic tracts were the left posterior thalamic radiation, left superior cerebellar peduncle and right uncinate fasciculus. Serum biomarkers could have avoided 1 in 5 DTI scans, with GFAP <12 h and NFL 12-24 - 24 h from injury performing best. Interpretation DTI substantially improved existing prognostic models for functional outcome in patients with mTBI and a normal CT, and biomarkers could help select patients for MRI. If validated, DTI could allow for targeted follow- up and enrichment of clinical trials of early interventions to improve outcome.

Introduction: A blood-based biomarker (BBBM) test could help to better stratify patients with traumatic brain injury (TBI), reduce unnecessary imaging, to detect and treat secondary insults, predict outcomes, and monitor treatment effects and quality of care. Research question: What evidence is available for clinical applications of BBBMs in TBI and how to advance this field? Material and methods: This narrative review discusses the potential clinical applications of core BBBMs in TBI. A literature search in PubMed, Scopus, and ISI Web of Knowledge focused on articles in English with the words “traumatic brain injury” together with the words “blood biomarkers”, “diagnostics”, “outcome prediction”, “extracranial injury” and “assay method” alone-, or in combination. Results: Glial fibrillary acidic protein (GFAP) combined with Ubiquitin C-terminal hydrolase-L1(UCH-L1) has received FDA clearance to aid computed tomography (CT)-detection of brain lesions in mild (m) TBI. Application of S100B led to reduction of head CT scans. GFAP may also predict magnetic resonance imaging (MRI) abnormalities in CT-negative cases of TBI. Further, UCH-L1, S100B, Neurofilament light (NF-L), and total tau showed value for predicting mortality or unfavourable outcome. Nevertheless, biomarkers have less role in outcome prediction in mTBI. S100B could serve as a tool in the multimodality monitoring of patients in the neurointensive care unit. Discussion and conclusion: Largescale systematic studies are required to explore the kinetics of BBBMs and their use in multiple clinical groups. Assay development/cross validation should advance the generalizability of those results which implicated GFAP, S100B and NF-L as most promising biomarkers in the diagnostics of TBI.

The Scandinavian NeuroTrauma Committee (SNC) guidelines recommend S100 calcium-binding protein B (S100B) as a screening tool for early detection of Traumatic brain injury (TBI) in patients presenting with an initial Glasgow Coma Scale (GCS) of 14-15. The objective of the current study was to compare S100B's diagnostic performance within the recommended 6-h window after injury, compared with glial fibrillary acidic protein (GFAP) and UCH-L1. The secondary outcome of interest was the ability of these biomarkers in detecting traumatic intracranial pathology beyond the 6-h mark. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) core database (2014-2017) was queried for data pertaining to all TBI patients with an initial GCS of 14-15 who had a blood sample taken within 6 h of injury in which the levels of S100B, GFAP, and UCH-L1 were measured. As a subgroup analysis, data involving patients with blood samples taken within 6-9 h and 9-12 h were analyzed separately for diagnostic ability. The diagnostic ability of these biomarkers for detecting any intracranial injury was evaluated based on the area under the receiver operating characteristic curve (AUC). Each biomarker's sensitivity, specificity, and accuracy were also reported at the cutoff that maximized Youden's index. A total of 531 TBI patients with GCS 14-15 on admission had a blood sample taken within 6 h, of whom 24.9% (n = 132) had radiologically confirmed intracranial injury. The AUCs of GFAP (0.86, 95% confidence interval [CI]: 0.82-0.90) and UCH-L1 (0.81, 95% CI: 0.76-0.85) were statistically significantly higher than that of S100B (0.74, 95% CI: 0.69-0.79) during this time. There was no statistically significant difference in the predictive ability of S100B when sampled within 6 h, 6-9 h, and 9-12 h of injury, as the p values were >0.05 when comparing the AUCs. Overlapping AUC 95% CI suggests no benefit of a combined GFAP and UCH-L1 screening tool over GFAP during the time periods studied [0.87 (0.83-0.90) vs. 0.86 (0.82-0.90) when sampled within 6 h of injury, 0.83 (0.78-0.88) vs. 0.83 (0.78-0.89) within 6 to 9 h and 0.81 (0.73-0.88) vs. 0.79 (0.72-0.87) within 9-12 h]. Targeted analysis of the CENTER-TBI core database, with focus on the patient category for which biomarker testing is recommended by the SNC guidelines, revealed that GFAP and UCH-L1 perform superior to S100B in predicting CT-positive intracranial lesions within 6 h of injury. GFAP continued to exhibit superior predictive ability to S100B during the time periods studied. S100B displayed relatively unaltered screening performance beyond the diagnostic timeline provided by SNC guidelines. These findings suggest the need for a reevaluation of the current SNC TBI guidelines.

Traumatic brain injury (TBI) is among the main causes of sudden death after head trauma. These injuries can result in severe degeneration and neuronal cell death in the CNS, including the retina, which is a crucial part of the brain responsible for perceiving and transmitting visual information. The long-term effects of mild-repetitive TBI (rmTBI) are far less studied thus far, even though damage induced by repetitive injuries occurring in the brain is more common, especially amongst athletes. rmTBI can also have a detrimental effect on the retina and the pathophysiology of these injuries is likely to differ from severe TBI (sTBI) retinal injury. Here, we show how rmTBI and sTBI can differentially affect the retina. Our results indicate an increase in the number of activated microglial cells and Caspase3-positive cells in the retina in both traumatic models, suggesting a rise in the level of inflammation and cell death after TBI. The pattern of microglial activation appears distributed and widespread but differs amongst the various retinal layers. sTBI induced microglial activation in both the superficial and deep retinal layers. In contrast to sTBI, no significant change occurred following the repetitive mild injury in the superficial layer, only the deep layer (spanning from the inner nuclear layer to the outer plexiform layer) shows microglial activation. This difference suggests that alternate response mechanisms play a role in the case of the different TBI incidents. The Caspase3 activation pattern showed a uniform increase in both the superficial and deep layers of the retina. This suggests a different action in the course of the disease in sTBI and rmTBI models and points to the need for new diagnostic procedures. Our present results suggest that the retina might serve as such a model of head injuries since the retinal tissue reacts to both forms of TBI and is the most accessible part of the human brain.

IntroductionMild traumatic brain injury (mTBI) and hypertension synergize to induce persistent disruption of the blood–brain barrier (BBB), neuroinflammation and cognitive decline. However, the underlying mechanisms are not known. Cerebral production of Cyclophilin A (CyPA) is induced in hypertension and after TBI, and it was demonstrated to activate the nuclear factor-κB (NF-kB)- matrix-metalloproteinase-9 (MMP-9) pathway in cerebral vessels leading to BBB disruption.MethodsTo test the role of CyPA in mTBI- and hypertension-induced BBB disruption we induced mTBI in normotensive and spontaneously hypertensive rats (SHR), then the animals were treated with cyclosporine A (a specific inhibitor of CyPA production) or vehicle for 7 days. We assessed BBB permeability and integrity, cerebral expression and activity of the CyPA-NF-kB-MMP-9 pathway, extravasation of fibrin and neuroinflammation.ResultsWe found that mild TBI induced BBB disruption and upregulation of the CyPA-NF-kB-MMP-9 pathway in hypertension, which were prevented by blocking CyPA. Cyclosporine treatment and preservation of BBB function prevented accumulation of blood-derived fibrin in the brain parenchyma of hypertensive rats after mTBI and reversed increased neuroinflammation.DiscussionWe propose that mTBI and hypertension interact to promote BBB disruption via the CyPA-NF-kB-MMP-9 pathway, and inhibition of cyclophilin production after mTBI may exert neuroprotection and improve cognitive function in hypertensive patients.

Prognostication is challenging in patients with traumatic brain injury (TBI) in whom computed tomography (CT) fails to fully explain a low level of consciousness. Serum biomarkers reflect the extent of structural damage in a different way than CT does, but it is unclear whether biomarkers provide additional prognostic value across the range of CT abnormalities. This study aimed to determine the added predictive value of biomarkers, differentiated by imaging severity. This prognostic study used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study (2014-2017). The analysis included patients aged & GE;16 years with a moderate-severe TBI (Glasgow Coma Scale [GCS] <13) who had an acute CT and serum biomarkers obtained & LE;24h of injury. Of six protein biomarkers (GFAP, NFL, NSE, S100B, Tau, UCH-L1), the most prognostic panel was selected using lasso regression. The performance of established prognostic models (CRASH and IMPACT) was assessed before and after the addition of the biomarker panel and compared between patients with different CT Marshall scores (Marshall score <3 vs. Marshall score & GE;3). Outcome was assessed at six months post-injury using the extended Glasgow Outcome Scale (GOSE), and dichotomized into favorable and unfavorable (GOSE <5). We included 872 patients with moderate-severe TBI. The mean age was 47 years (range 16-95); 647 (74%) were male and 438 (50%) had a Marshall CT score <3. The serum biomarkers GFAP, NFL, S100B and UCH-L1 provided complementary prognostic information; NSE and Tau showed no added value. The addition of the biomarker panel to established prognostic models increased the area under the curve (AUC) by 0.08 and 0.03, and the explained variation in outcome by 13-14% and 7-8%, for patients with a Marshall score of <3 and & GE;3, respectively. The incremental AUC of biomarkers for individual models was significantly greater when the Marshall score was <3 compared with & GE;3 (p < 0.001). Serum biomarkers improve outcome prediction after moderate-severe TBI across the range of imaging severities and especially in patients with a Marshall score <3.