Introduction: Glial fibrillary acidic protein (GFAP) may serve as a serum marker of traumatic brain injury (TBI) that can be used to monitor biochemical changes in patients and gauge the response to treatment. However, the temporal profile of serum GFAP in the acute period of brain injury and the associated utility for outcome prediction has not been elucidated.Methods: We conducted a prospective longitudinal cohort study of consecutive severe TBI patients in a local tertiary neurotrauma center in Shanghai, China, between March 2011 and September 2014. All patients were monitored and managed with a standardized protocol with inclusion of hypothermia and other intensive care treatments. Serum specimens were collected on admission and then daily for the first 5 days. GFAP levels were measured using enzyme-linked immunosorbent assay techniques. Patient outcome was assessed at 6 months post injury with the Glasgow Outcome Scale and further grouped into death versus survival and unfavorable versus favorable.Results: A total of 67 patients were enrolled in the study. The mean time from injury to admission was 2.6 hours, and the median admission Glasgow Coma Scale score was 6. Compared with healthy subjects, patients with severe TBI had increased GFAP levels on admission and over the subsequent 5 days post injury. Serum GFAP levels showed a gradual reduction from admission to day 3, and then rebounded on day 4 when hypothermia was discontinued with slow rewarming. GFAP levels were significantly higher in patients who died or had an unfavorable outcome across all time points than in those who were alive or had a favorable outcome. Results of receiver operating characteristic curve analysis indicated that serum GFAP at each time point could predict neurological outcome at 6 months. The areas under the curve for GFAP on admission were 0.761 for death and 0.823 for unfavorable outcome, which were higher than those for clinical variables such as age, Glasgow Coma Scale score, and pupil reactions.Conclusions: Serum GFAP levels on admission and during the first 5 days of injury were increased in patients with severe TBI and were predictive of neurological outcome at 6 months.

Traumatic brain injury (TBI) causes a primary insult and initiates a secondary injury cascade. The mechanisms underlying the secondary injury are multifactorial and may include the aberrant expression of long non-coding RNA (lncRNA) post-TBI. Here, lncRNA microarray analysis was performed to profile the altered lncRNAs in the rat hippocampus after TBI. A total of 271 lncRNA probe sets and 1046 messenger RNA (mRNA) probe sets were differentially expressed after TBI. Gene ontology analysis showed that the main components of the most significantly changed categories were inflammation, DNA transcription, apoptosis, and necroptosis. Additionally, the pathway analysis and the pathway relation network revealed correlated pathways mainly involving inflammation, cell cycle, and apoptosis. A co-expression network of these aberrantly expressed lncRNAs and mRNAs was further constructed to predict the potential function of individual lncRNAs. Sub–co-expression networks were formed for the top three lncRNAs: NR_002704, ENSRNOT00000062543, and Zfas1. Thus, our study demonstrated differential expression of a series of lncRNAs in the rat hippocampus after TBI, which may be correlated with post-TBI physiological and pathological processes. The findings also may provide novel targets for further investigation of both the molecular mechanisms underlying TBI and potential therapeutic interventions.

Circular RNAs (circRNAs) are involved in a variety of diseases. However, the roles of circRNAs in traumatic brain injury (TBI) remain unknown. In this study, circRNA microarray was used to profile the altered circRNAs in the rat hippocampus following TBI. A total of 192 circRNAs were observed to be differentially expressed (FC ≥1.5 and P <0.05) after TBI ,including 98 up-regulated and 94 down-regulated. Gene ontology (GO) and KEGG pathway analysis indicated that many mRNAs transcribed from the host genes of altered circRNAs were implicated in brain damage and neural regeneration. CircRNA/miRNA interaction was predicted using Arraystar’s home-made miRNA target prediction software based on TargetScan and miRanda. Thus, our studies have demonstrated altered circRNA expression pattern in the rat hippocampus after TBI, which may play important roles in post-TBI physiological and pathological processes. These findings may provide not only a new direction for studying the molecular mechanisms underlying TBI but also new possibility for the treatment of TBI by modulating circRNAs.

Severe traumatic brain injury (sTBI) is extremely disabling and associated with high mortality. Early detection of patients at risk of short-term (≤14 days after injury) death and provision of timely treatment is critical. This study aimed to establish and independently validate a nomogram to estimate individualised short-term mortality for sTBI based on large-scale data from China. The data were from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) China registry (between Dec 22, 2014, and Aug 1, 2017; registered at ClinicalTrials.gov, NCT02210221). This analysis included information of eligible patients with diagnosed sTBI from 52 centres (2631 cases). 1808 cases from 36 centres were enrolled in the training group (used to construct the nomogram) and 823 cases from 16 centres were enrolled in the validation group. Multivariate logistic regression was used to identify independent predictors of short-term mortality and establish the nomogram. The discrimination of the nomogram was evaluated using area under the receiver operating characteristic curves (AUC) and concordance indexes (C-index), the calibration was evaluated using calibration curves and Hosmer–Lemeshow tests (H-L tests). Decision curve analysis (DCA) was used to evaluate the net benefit of the model for patients. In the training group, multivariate logistic regression demonstrated that age (odds ratio [OR] 1.013, 95% confidence interval [CI] 1.003−1.022), Glasgow Coma Scale score (OR 33.997, 95% CI 14.657−78.856), Injury Severity Score (OR 1.020, 95% CI 1.009−1.032), abnormal pupil status (OR 1.738, 95% CI 1.178−2.565), midline shift (OR 2.266, 95% CI 1.378−3.727), and pre-hospital intubation (OR 2.059, 95% CI 1.472−2.879) were independent predictors for short-term death in patients with sTBI. A nomogram was built using the logistic regression prediction model. The AUC and C-index were 0.859 (95% CI 0.837–0.880). The calibration curve of the nomogram was close to the ideal reference line, and the H-L test p value was 0.504. DCA curve demonstrated significantly better net benefit with the model. Application of the nomogram in external validation group still showed good discrimination (AUC and C-index were 0.856, 95% CI 0.827–0.886), calibration, and clinical usefulness. A nomogram was developed for predicting the occurrence of short-term (≤14 days after injury) death in patients with sTBI. This can provide clinicians with an effective and accurate tool for the early prediction and timely management of sTBI, as well as support clinical decision-making around the withdrawal of life-sustaining therapy. This nomogram is based on Chinese large-scale data and is especially relevant to low- and middle-income countries. 10.13039/501100012247 Shanghai Academic Research Leader (21XD1422400), Shanghai Medical and Health Development Foundation (20224Z0012).