Background In order to improve injury assessment of brain injuries, protein markers of pathophysiological processes and tissue fate have been introduced in the clinic. The most studied protein “biomarker” of cerebral damage in traumatic brain injury (TBI) is the protein S100B. The aim of this narrative review is to thoroughly analyze the properties and capabilities of this biomarker with focus on clinical utility in the assessment of patients suffering from TBI. Results S100B has successfully been implemented in the clinic regionally (1) to screen mild TBI patients evaluating the need to perform a head computerized tomography, (2) to predict outcome in moderate-to-severe TBI patients, (3) to detect secondary injury development in brain-injured patients and (4) to evaluate treatment efficacy. The potential opportunities and pitfalls of S100B in the different areas usually refer to its specificity and sensitivity to detect and assess intracranial injury. Conclusion Given some shortcomings that should be realized, S100B can be used as a versatile screening, monitoring and prediction tool in the management of TBI patients.

Background: The proteins S100B, neuron-specific enolase (NSE), glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and neurofilament light (NF-L) have been serially sampled in serum of patients suffering from traumatic brain injury (TBI) in order to assess injury severity and tissue fate. We review the current literature of serum level dynamics of these proteins following TBI and used the term “effective half-life” (t½) in order to describe the “fall” rate in serum Material and methods: Through searches on EMBASE, Medline and Scopus, we looked for articles where these proteins had been serially sampled in serum in human TBI. We excluded animal studies, studies with only one presented sample and studies without neuroradiological examinations. Results: Following screening (10,389 papers), n=122 papers were included. The proteins S100B (n=66) and NSE (n=27) were the two most frequent biomarkers that were serially sampled. For S100B in severe TBI, a majority of studies indicate a t½ of about 24 hours, even if very early sampling in these patients reveals rapid decreases (1-2 hours) though possibly of non-cerebral origin. In contrast, the t½ for NSE is comparably longer, ranging from 48-72 hours in severe TBI cases. The protein GFAP (n=18) appears to have t½ of about 24-48 hours in severe TBI. The protein UCH-L1 (n=9) present a t½ around 7 hours in mild TBI, and about 10 hours in severe. Frequent sampling of these proteins revealed different trajectories with persisting high serum levels, or secondary peaks, in patients with unfavorable outcome or in patients developing secondary detrimental events. Finally, NF-L (n=2) only increased in the few studies available, suggesting a serum availability >10 days. To date, automated assays are available for S100B and NSE making them faster and more practical to use. Conclusion: Serial sampling of brain specific proteins in serum reveals different temporal trajectories that should be acknowledged. Proteins with shorter serum availability, like S100B, may be superior to proteins such as NF-L in detection of secondary harmful events when monitoring patients with TBI.

Brain-enriched protein biomarkers of tissue fate are being introduced clinically to aid in traumatic brain injury (TBI) management. The aim of this study was to determine how concentrations of six different protein biomarkers, measured in samples collected during the first weeks after TBI, relate to injury severity and outcome. We included neurocritical care TBI patients that were prospectively enrolled from 2007 to 2013, all having one to three blood samples drawn during the first 2 weeks. The biomarkers analyzed were S100 calcium-binding protein B (S100B), neuron-specific enolase (NSE), glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase-L1 (UCH-L1), tau, and neurofilament-light (NF-L). Glasgow Outcome Score (GOS) was assessed at 12 months. In total, 172 patients were included. All serum markers were associated with injury severity as classified on computed tomography scans at admission. Almost all biomarkers outperformed other known outcome predictors with higher levels the first 5 days, correlating with unfavorable outcomes, and UCH-L1 (0.260, pseduo- R ² ) displaying the best discrimination in univariate analyses. After adjusting for acknowledged TBI outcome predictors, GFAP and NF-L added most independent information to predict favorable/unfavorable GOS, improving the model from 0.38 to 0.51 pseudo- R ² . A correlation matrix indicated substantial covariance, with the strongest correlation between UCH-L1, GFAP, and tau ( r = 0.827–0.880). Additionally, the principal component analysis exhibited clustering of UCH-L1 and tau, as well as GFAP, S100B, and NSE, which was separate from NF-L. In summary, a panel of several different protein biomarkers, all associated with injury severity, with different cellular origin and temporal trajectories, improve outcome prediction models.

In order to improve assessment and outcome prediction in patients suffering from traumatic brain injury (TBI), cerebral protein levels in serum have been suggested as biomarkers of injury. However, despite much investigation, biomarkers have yet to reach broad clinical utility in TBI. This study is a 9-year follow-up and clinical experience of the two most studied proteins, neuron-specific enolase (NSE) and S100B, in a neuro-intensive care TBI population. Our aims were to investigate to what extent NSE and S100B, independently and in combination, could predict outcome, assess injury severity, and to investigate if the biomarker levels were influenced by extracranial factors. All patients treated at the neuro-intensive care unit at Karolinska University Hospital, Stockholm, Sweden between 2005 and 2013 with at least three measurements of serum S100B and NSE (sampled twice daily) were retrospectively included. In total, 417 patients fulfilled the criteria. Parameters were extracted from the computerized hospital charts. Glasgow Outcome Score (GOS) was used to assess long-term functional outcome. Univariate, and multivariate, regression models toward outcome and what explained the high levels of the biomarkers were performed. Nagelkerke’s pseudo-R2 was used to illustrate the explained variance of the different models. A sliding window assessed biomarker correlation to outcome and multitrauma over time. S100B was found a better predictor of outcome as compared to NSE (area under the curve (AUC) samples, the first 48 hours had Nagelkerke’s pseudo-R2 values of 0.132 and 0.038, respectively), where the information content of S100B peaks at approximately 1 day after trauma. In contrast, although both biomarkers were independently correlated to outcome, NSE had limited additional predictive capabilities in the presence of S100B in multivariate models, due to covariance between the two biomarkers (correlation coefficient 0.673 for AUC 48 hours). Moreover, NSE was to a greater extent correlated to multitrauma the first 48 hours following injury, whereas the effect of extracerebral trauma on S100B levels appears limited to the first 12 hours. While both biomarkers are independently correlated to long-term functional outcome, S100B is found a more accurate outcome predictor and possibly a more clinically useful biomarker than NSE for TBI patients.

Traumatic brain injury (TBI) is a common cause of death and disability, worldwide. Early determination of injury severity is essential to improve care. Neurofilament light (NF-L) has been introduced as a marker of neuroaxonal injury in neuroinflammatory/-degenerative diseases. In this study we determined the predictive power of serum (s-) and cerebrospinal fluid (CSF-) NF-L levels towards outcome, and explored their potential correlation to diffuse axonal injury (DAI). A total of 182 patients suffering from TBI admitted to the neurointensive care unit at a level 1 trauma center were included. S-NF-L levels were acquired, together with S100B and neuron-specific enolase (NSE). CSF-NF-L was measured in a subcohort (n = 84) with ventriculostomies. Clinical and neuro-radiological parameters, including computerized tomography (CT) and magnetic resonance imaging, were included in the analyses. Outcome was assessed 6 to 12 months after injury using the Glasgow Outcome Score (1-5). In univariate proportional odds analyses mean s-NF-L, -S100B and -NSE levels presented a pseudo-R² Nagelkerke of 0.062, 0.214 and 0.074 in correlation to outcome, respectively. In a multivariate analysis, in addition to a model including core parameters (pseudo-R² 0.33 towards outcome; Age, Glasgow Coma Scale, pupil response, Stockholm CT score, abbreviated injury severity score, S100B), S-NF-L yielded an extra 0.023 pseudo-R² and a significantly better model (p = 0.006) No correlation between DAI or CT assessed-intracranial damage and NF-L was found. Our study thus demonstrates that S-NF-L correlates to TBI outcome, even if used in models with S100B, indicating an independent contribution to the prediction, perhaps by reflecting different pathophysiological processes, not possible to monitor using conventional neuroradiology. Although we did not find a predictive value of NF-L for DAI, this cannot be completely excluded. We suggest further studies, with volume quantification of axonal injury, and a prolonged sampling time, in order to better determine the connection between NF-L and DAI.

Knowledge of the average size and variability of the human spinal cord can be of importance when treating pathological conditions in the spinal cord. Data on healthy human spinal cord morphometrics have been published for more than a century using different techniques of measurements, but unfortunately, comparison of results from different studies is difficult because of the different anatomical landmarks used as reference points along the craniocaudal axis for the measurements. The aim of this review was to compute population estimates of the transverse and anteroposterior diameter of the human spinal cord by comparing and combining previously published data on a normalized craniocaudal axis. We included eleven studies presenting measurements of spinal cord cross-sectional diameters, with a combined sample size ranging from 15 to 488 subjects, depending on spinal cord level. Based on five published studies presenting data on the lengths of the segments of the spinal cord and vertebral column, we calculated the relative positions of all spinal cord neuronal segments and vertebral bony segments and mapped measurements of spinal cord size to a normalized craniocaudal axis. This mapping resulted in better alignment between studies and allowed the calculation of weighted averages and standard deviations along the spinal cord. These weighted averages were smoothed using a generalized additive model to yield continuous population estimates for transverse and anteroposterior diameter and associated standard deviations. The spinal cord had the largest transverse diameter at spinal cord neuronal segment C5 (13.3 +/-2.2), decreased to segment T8 (8.3 +/-2.1), and increased slightly again to 9.4 +/-1.5 at L3. The anteroposterior diameter showed less variation in size along the spinal cord at C5 (7.4 +/- 1.6), T8 (6.3 +/- 2.0), and L3 (7.5 +/- 1.6). All estimates are presented in millimeters +/- 2 standard deviations. We conclude that segmental transverse and anteroposterior diameters of the healthy human spinal cord from different published sources can be combined on a normalized craniocaudal axis and yield meaningful population estimates. These estimates could be useful in routine management of patients with neurodegenerative diseases as well as for clinical research and experimental applications aimed at surgical spinal cord repair.