Rotarod motor performance and advanced spinal cord lesion image analysis refine assessment of neurodegeneration in experimental autoimmune encephalomyelitis

Robert Berg, JD Laman, Marjan van Meurs, Rogier Hintzen, CC Hoogenraad

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)


Background: Experimental autoimmune encephalomyelitis (EAE) is a commonly used experimental model for multiple sclerosis (MS). Experience with this model mainly comes from the field of immunology, while data on its use in studying the neurodegenerative aspects of MS is scarce. New method: The aim of this study is to improve and refine methods to assess neurodegeneration and function in EAE. Using the rotarod, a tool used in neuroscience to monitor motor performance, we evaluated the correlation between motor performance, disease severity as measured using a clinical scale and area covered by inflammatory lesions. Results: The included parameters are highly correlated in a non-linear manner, with motor performance rapidly decreasing in the intermediate values of the clinical scale. The relation between motor performance and histopathological damage is exclusively determined by lesions in the ventral and lateral columns, based on a new method of analysis of the entire spinal cord. Using a set of definitions for distinct disease milestones, we quantified disease duration as well as severity. Comparison with existing methods: The rotarod measures motor performance in a more objective and quantitative manner compared to using a clinical score. The outcome showes a strong correlation to the surface area of inflammatory lesions in the motor systems of the spinal cord. Conclusions: These results provide an improved workflow for interpreting the outcome of EAE from a neurological point of view, with the eventual goal of dissecting neurodegeneration and evaluating neuroprotective drugs in EAE for application in MS. (C) 2016 Elsevier B.V. All rights reserved.
Original languageUndefined/Unknown
Pages (from-to)66-76
Number of pages11
JournalJournal of Neuroscience Methods
Publication statusPublished - 2016

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