Study Shows Consistent Evidence of Axonal Injury Following A Single TBI For Years After Injury
American Academy of Neurology publishes an important study showing consistent evidence of axonal injury following a single TBI for years after injury using multiple measures, including a blood biomarker, MRI/DTI and volumetric analysis, and functional tests
On July 8, 2020 the American Academy of Neurology published an important study advancing our understanding of, and ability to diagnose, traumatic brain injury (TBI). The study, Shahim P, Politis A, van der Merwe A, et al. Time course and diagnostic utility of NfL, tau, GFAp, and UCH-L1 in subacute and chronic TBI was published online ahead of print, 2020 Jul 8 in Neurology. Funding for the study was provided by the National Institutes of Health and the Department of Defense (Center for Neuroscience and Regenerative Medicine.)
The authors of the study conclude as follows:
“ In summary, these findings suggest that a single mild to moderate TBI may cause long-term neuroaxonal degeneration and astrogliosis/activation.”
The study found one biomarker, “serum NfL”, to be “highly sensitive” in detecting neuroaxonal degeneration following subacute and chronic TBI. NfL is a protein released into the blood and cerebral spinal fluid when neurons are damaged. (NfL levels have been used as a tool to detect brain damage with other neurodegenerative conditions such as MS, Alzheimers and ALS.)
What is particularly significant about this study is that levels of serum NfL correlated closely with other measures of damage, including MRI/DTI and volumetric analysis and functional tests. Levels of serum NfL distinguished patients with mild, moderate and severe TBI from each other and compared to controls (without injury) for months to years after injury.
These findings suggest that serum NfL may be a important tool to determine prognosis after a TBI, to facilitate the development of therapies and to guide treatment decisions. Further research is needed, the authors suggest, to “standardize methods of quantification across analytic platforms and determine cut-offs across age and different injury subtypes.”