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. 2018 Dec;84(6):829-842.
doi: 10.1002/ana.25365. Epub 2018 Nov 30.

Meningeal inflammation and cortical demyelination in acute multiple sclerosis

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Free article

Meningeal inflammation and cortical demyelination in acute multiple sclerosis

Ryan J Bevan et al. Ann Neurol. 2018 Dec.
Free article

Abstract

Objective: Cortical gray matter (GM) pathology, involving demyelination and neurodegeneration, associated with meningeal inflammation, could be important in determining disability progression in multiple sclerosis (MS). However, we need to know more about how cortical demyelination, neurodegeneration, and meningeal inflammation contribute to pathology at early stages of MS to better predict long-term outcome.

Methods: Tissue blocks from short disease duration MS (n = 12, median disease duration = 2 years), progressive MS (n = 21, disease duration = 25 years), non-diseased controls (n = 11), and other neurological inflammatory disease controls (n = 6) were quantitatively analyzed by immunohistochemistry, immunofluorescence, and in situ hybridization.

Results: Cortical GM demyelination was extensive in some cases of acute MS (range = 1-48% of total cortical GM), and subpial lesions were the most common type (62%). The numbers of activated (CD68+ ) microglia/macrophages were increased in cases with subpial lesions, and the density of neurons was significantly reduced in acute MS normal appearing and lesion GM, compared to controls (p < 0.005). Significant meningeal inflammation and lymphoid-like structures were seen in 4 of 12 acute MS cases. The extent of meningeal inflammation correlated with microglial/macrophage activation (p < 0.05), but not the area of cortical demyelination, reflecting the finding that lymphoid-like structures were seen adjacent to GM lesions as well as areas of partially demyelinated/remyelinated, cortical GM.

Interpretation: Our findings demonstrate that cortical demyelination, neuronal loss, and meningeal inflammation are notable pathological hallmarks of acute MS and support the need to identify early biomarkers of this pathology to better predict outcome. Ann Neurol 2018;84:829-842.

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