Objective This study examined whether serum levels of GFAP breakdown products (GFAP-BDP) were elevated in mild and moderate TBI compared to controls and if they were associated with traumatic intracranial lesions on CT scan (+CT) and having a neurosurgical intervention (NSI). Methods This prospective cohort study enrolled adult patients presenting to three Level 1 Trauma Centers following blunt head trauma with loss of consciousness, amnesia, or disorientation and a GCS 9–15. Control groups included normal uninjured controls and trauma controls presenting to the ED with orthopedic injuries or an MVC without TBI. Blood samples were obtained in all patients within 4 hours of injury and measured by ELISA for GFAP-BDP (ng/ml). Results Of the 307 patients enrolled, 108 were TBI patients (97 with GCS 13–15, and 11 with GCS 9–12) and 199 were controls (176 normal controls and 16 MVC controls and 7 orthopedic controls). ROC curves demonstrated that early GFAP-BDP levels were able to distinguish TBI from uninjured controls with an AUC of 0.90 (95%CI 0.86–0.94) and differentiated TBI with a GCS 15 with an AUC 0.88 (95%CI 0.82–0.93). Thirty two TBI patients (30%) had lesions on CT. The AUC for discriminating those patients with CT lesions versus those without CT lesions was 0.79 (95%CI 0.69–0.89). Moreover, the ROC curve for distinguishing NSI from no NSI yielded an AUC of 0.87 (95%CI 0.77–0.96). Conclusions GFAP-BDP is detectable in serum within an hour of injury and is associated with measures of injury severity including the GCS score, CT lesions and neurosurgical intervention. Further study is required to validate these findings before clinical application.

No abstract

The role of systemic autoimmunity in human traumatic brain injury (TBI) and other forms of brain injuries is recognized but not well understood. In this study, a systematic investigation was performed to identify serum autoantibody responses to brain-specific proteins after TBI in humans. TBI autoantibodies showed predominant immunoreactivity against a cluster of bands from 38–50 kDa on human brain immunoblots, which were identified as GFAP and GFAP breakdown products. GFAP autoantibody levels increased by 7 days after injury, and were of the IgG subtype predominantly. Results from in vitro tests and rat TBI experiments also indicated that calpain was responsible for removing the amino and carboxyl termini of GFAP to yield a 38 kDa fragment. Additionally, TBI autoantibody staining co-localized with GFAP in injured rat brain and in primary rat astrocytes. These results suggest that GFAP breakdown products persist within degenerating astrocytes in the brain. Anti-GFAP autoantibody also can enter living astroglia cells in culture and its presence appears to compromise glial cell health. TBI patients showed an average 3.77 fold increase in anti-GFAP autoantibody levels from early (0–1 days) to late (7–10 days) times post injury. Changes in autoantibody levels were negatively correlated with outcome as measured by GOS-E score at 6 months, suggesting that TBI patients with greater anti-GFAP immune-responses had worse outcomes. Due to the long lasting nature of IgG, a test to detect anti-GFAP autoantibodies is likely to prolong the temporal window for assessment of brain damage in human patients.

Head computed tomography (CT) imaging is still a commonly obtained diagnostic test for patients with minor head injury despite availability of clinical decision rules to guide imaging use and recommendations to reduce radiation exposure resulting from unnecessary imaging. This prospective multicenter observational study of 251 patients with suspected mild to moderate traumatic brain injury (TBI) evaluated three serum biomarkers' (glial fibrillary acidic protein [GFAP], ubiquitin C-terminal hydrolase-L1 [UCH-L1] and S100B measured within 6 h of injury) ability to differentiate CT negative and CT positive findings. Of the 251 patients, 60.2% were male and 225 (89.6%) had a presenting Glasgow Coma Scale score of 15. A positive head CT (intracranial injury) was found in 36 (14.3%). UCH-L1 was 100% sensitive and 39% specific at a cutoff value >40 pg/mL. To retain 100% sensitivity, GFAP was 0% specific (cutoff value 0 pg/mL) and S100B had a specificity of only 2% (cutoff value 30 pg/mL). All three biomarkers had similar values for areas under the receiver operator characteristic curve: 0.79 (95% confidence interval; 0.70–0.88) for GFAP, 0.80 (0.71–0.89) for UCH-L1, and 0.75 (0.65–0.85) for S100B. Neither GFAP nor UCH-L1 curve values differed significantly from S100B (p = 0.21 and p = 0.77, respectively). In our patient cohort, UCH-L1 outperformed GFAP and S100B when the goal was to reduce CT use without sacrificing sensitivity. UCH-L1 values <40 pg/mL could potentially have aided in eliminating 83 of the 215 negative CT scans. These results require replication in other studies before the test is used in actual clinical practice.

Outcome prediction following severe traumatic brain injury (sTBI) is a widely investigated field of research. A major breakthrough is represented by the IMPACT prognostic calculator based on admission data of more than 8500 patients. A growing body of scientific evidence has shown that clinically meaningful biomarkers, including glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), and aII-spectrin breakdown product (SBDP145), could also contribute to outcome prediction. The present study was initiated to assess whether the addition of biomarkers to the IMPACT prognostic calculator could improve its predictive power. Forty-five sTBI patients (GCS score £ 8) from four different sites were investigated. We utilized the core model of the IMPACT calculator (age, GCS motor score, and reaction of pupils), and measured the level of GFAP, UCH-L1, and SBDP145 in serum and cerebrospinal fluid (CSF). The forecast and actual 6-month outcomes were compared by logistic regression analysis. The results of the core model itself, as well as serum values of GFAP and CSF levels of SBDP145, showed a significant correlation with the 6-month mortality using a univariate analysis. In the core model, the Nagelkerke R 2 value was 0.214. With multivariate analysis we were able to increase this predictive power with one additional biomarker (GFAP in CSF) to R 2 = 0.476, while the application of three biomarker levels (GFAP in CSF, GFAP in serum, and SBDP145 in CSF) increased the Nagelkerke R 2 to 0.700. Our preliminary results underline the importance of biomarkers in outcome prediction, and encourage further investigation to expand the predictive power of contemporary outcome calculators and prognostic models in TBI.