Endre Czeiter

Traumatic brain injury (TBI) induces rapid neuroinflammatory responses not only in the brain but also in anatomically and immunologically connected central nervous system (CNS) compartments, including the retina. In our study, we investigated retinal microglial activation, retinal ganglion cell (RGC) calcium dynamics, and caspase-3 activation in adult mice subjected to severe traumatic brain injury using the Marmarou impact-acceleration model at 24 and 48 h post-injury. Carrying out Ca²⁺-imaging, immunohistochemistry, and ex vivo time-lapse microscopy, we found robust microglial activation in both the superficial and deep retinal layers following TBI, accompanied by increased microglial motility. RGCs exhibited a transient surge in degeneration-induced spontaneous activity at 24 h, followed by a marked reduction below control levels at 48 h, consistent with early degenerative changes. Activated caspase-3 levels were significantly elevated in both microglia and other retinal cell types at both time points, indicating ongoing apoptotic effects. Together, these findings demonstrate that TBI rapidly triggers inflammatory and apoptotic mechanisms in the retina, which are detectable within the first 48 hours. Our results highlight the retina as a sensitive indicator of early CNS pathology after traumatic injury and underscore the potential of retinal analysis for monitoring TBI-induced neurodegeneration for future clinical implementation. Graphical

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.

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.

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.”

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. 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]). 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). 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.

Introduction: The Scandinavian NeuroTrauma Committee (SNC) guidelines recommend 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-hour window after injury, compared to GFAP and UCH-L1. The secondary outcome of interest was the ability of these biomarkers in detecting traumatic intracranial pathology beyond the 6-hour mark. Methods: The 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 hours 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 hours, and 9-12 hours 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. Results: A total of 531 TBI patients with GCS 14-15 on admission had a blood sample taken within 6 hours, 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 hours, 6-9 hours, and 9-12 hours 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 hours of injury, 0.83 (0.78-0.88) vs 0.83 (0.78-0.89) within 6-to-9 hours and 0.81 (0.73-0.88) vs 0.79 (0.72-0.87) within 9-12 hours]. Conclusions: 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 hours 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 re-evaluation of the current SNC TBI guidelines.

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 ≥16 years with a moderate-severe TBI (Glasgow Coma Scale [GCS] 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.

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.