Citation

Li Y, Zhang L, Kallakuri S, Cohen A, Cavanaugh JM. J. Neurol. Sci. 2015; 359(1-2): 280-286.

Affiliation

Department of Biomedical Engineering, Wayne State University, 818 W. Hancock Street, Detroit, MI 48201, United States.

Copyright

(Copyright © 2015, Elsevier Publishing)

DOI

10.1016/j.jns.2015.08.035

PMID

26671128

Abstract

A modified Marmarou impact acceleration model was used to help screen biomarkers to assess brain injury severity. Anesthetized male Sprague-Dawley rats were subjected to a closed head injury from 1.25, 1.75 and 2.25m drop heights. Linear and angular responses of the head were measured in vivo. 24h after impact, cerebrospinal fluid (CSF) and serum were collected. CSF and serum levels of phosphorylated neurofilament heavy (pNF-H), glial fibrillary acidic protein (GFAP), interleukin 6 (IL-6), and amyloid beta (Aβ) 1-42 were assessed by enzyme-linked immunosorbent assay (ELISA). Compared to controls, significantly higher CSF and serum pNF-H levels were observed in all impact groups, except between 1.25m and control in serum. Furthermore, CSF and serum pNF-H levels were significantly different between the impact groups. For GFAP, both CSF and serum levels were significantly higher at 2.25m compared to 1.75m, 1.25m and controls. There was no significant difference in CSF and serum GFAP levels between 1.75m and 1.25m, although both groups were significantly higher than control. TBI rats also showed significantly higher levels of IL-6 versus control in both CSF and serum, but no significant difference was observed between each impact group. Levels of Aβ were not significantly different between groups. Pearson's correlation analysis showed pNF-H and GFAP levels in CSF and serum had positive correlation with power (rate of impact energy), followed by average linear acceleration and surface righting (p<0.01), which were good predictors for traumatic axonal injury according to histologic assessment in our previous study, suggesting that they are directly related to the injury mechanism. The model used in this study showed a unique ability in elucidating the relationship between biomarker levels and severity of the mechanical trauma to the brain.

Language: en