Preventing chronic disease deterioration is an unmet need in people with multiple sclerosis, where axonal loss is considered a key substrate of disability. Clinically, chronic multiple sclerosis often presents as progressive myelopathy. Spinal cord cross-sectional area (CSA) assessed using MRI predicts increasing disability and has, by inference, been proposed as an indirect index of axonal degeneration. However, the association between CSA and axonal loss, and their correlation with demyelination, have never been systematically investigated using human post mortem tissue. We extensively sampled spinal cords of seven women and six men with multiple sclerosis (mean disease duration5 29 years) and five healthy controls to quantify axonal density and its association with demyelination and CSA. 396 tissue blocks were embedded in paraffin and immuno-stained for myelin basic protein and phosphorylated neurofilaments. Measurements included total CSA, areas of (i) lateral cortico-spinal tracts, (ii) gray matter, (iii) white matter, (iv) demyelination, and the number of axons within the lateral cortico-spinal tracts. Linear mixed models were used to analyze relationships. In multiple sclerosis CSA reduction at cervical, thoracic and lumbar levels ranged between 19 and 24% with white (19-24%) and gray (17-21%) matter atrophy contributing equally across levels. Axonal density in multiple sclerosis was lower by 57-62% across all levels and affected all fibers regardless of diameter. Demyelination affected 24-48% of the gray matter, most extensively at the thoracic level, and 11-13% of the white matter, with no significant differences across levels. Disease duration was associated with reduced axonal density, however not with any area index. Significant association was detected between focal demyelination and decreased axonal density. In conclusion, over nearly 30 years multiple sclerosis reduces axonal density by 60% throughout the spinal cord. Spinal cord cross sectional area, reduced by about 20%, appears to be a poor predictor of axonal density. AbbreviationsaCST 5 cortico-spinal tract area; CDD 5 chronic disease deterioration; CoV 5 coefficient of variation; CSA 5 cross sectional area; CST 5 Lateral corticospinal tract; EDSS 5 expanded disability status scale; GM 5 gray matter; MBP 5 myelin basic protein; WM 5 white matter.

(2017) Neuropathology and Applied Neurobiology Neuronal loss, demyelination and volume change in the multiple sclerosis neocortex Aims: Indices of brain volume [grey matter, white matter (WM), lesions] are being used as outcomes in clinical trials of patients with multiple sclerosis (MS). We investigated the relationship between cortical volume, the number of neocortical neurons estimated using stereology and demyelination. Methods: Nine MS and seven control hemispheres were dissected into coronal slices. On sections stained for Giemsa, the cortex was outlined and optical disectors applied using systematic uniform random sampling. Neurons were counted using an oil immersion objective (9 60) following stereological principles. Grey and WM demyelination was outlined on myelin basic protein immunostained sections, and expressed as percentages of cortex and WM respectively. Results: In MS, the mean number of neurons was 14.9 AE 1.9 billion vs. 24.4 AE 2.4 billion in controls (P < 0.011), a 39% difference. The density of neurons was smaller by 28% (P < 0.001) and cortical volume by 26% (P = 0.1). Strong association was detected between number of neurons and cortical volume (P < 0.0001). Demyelination affected 40 AE 13% of the MS neocortex and 9 AE 12% of the WM, however, neither correlated with neuronal loss. Only weak association was detected between number of neurons and WM volume. Conclusion: Neocortical neuronal loss in MS is massive and strongly predicted by cortical volume. Cortical volume decline detected in vivo may be similarly indicative of neuronal loss. Lack of association between neuronal density and demyelination suggests these features are partially independent, at least in chronic MS.

Disability in multiple sclerosis (MS) is considered primarily a result of axonal loss. However, correlation with spinal cord cross‐sectional area—a predictor of disability—is poor, questioning the unique role of axonal loss. We investigated the degree of synaptic loss in postmortem spinal cords (18 chronic MS, 8 healthy controls) using immunohistochemistry for synaptophysin and synapsin. Substantial (58–96%) loss of synapses throughout the spinal cord was detected, along with moderate (47%) loss of anterior horn neurons, notably in demyelinating MS lesions. We conclude that synaptic loss is significant in chronic MS, likely contributing to disability accrual. ANN NEUROL 2020;88:619–625

Multiple sclerosis (MS) is a common inflammatory, demyelinating and degenerative disease of the central nervous system. The majority of people with MS present with symptoms due to spinal cord damage, and in more advanced MS a clinical syndrome resembling that of progressive myelopathy is not uncommon. Significant efforts have been undertaken to predict MS-related disability based on short-term observations, for example, the spinal cord cross-sectional area measured using MRI. The histo-pathological correlates of spinal cord MRI changes in MS are incompletely understood, however a surge of interest in tissue microstructure has recently led to new approaches to improve the precision with which MRI indices relate to underlying tissue features, such as myelin content, neurite density and orientation, among others. Quantitative MRI techniques including T and T, magnetisation transfer (MT) and a number of diffusion-derived indices have all been successfully applied to post mortem MS spinal cord. Combining advanced quantification of histological features with quantitative - particularly diffusion-based - MRI techniques provide a new platform for high-quality MR/pathology data generation. To more accurately quantify grey matter pathology in the MS spinal cord, a key driver of physical disability in advanced MS, remains an important challenge of microstructural imaging.