Modeling the Relationship among Gray Matter Atrophy, Abnormalities in Connecting White Matter, and Cognitive Performance in Early Multiple Sclerosis

Abstract

Background and PurposeQuantitative assessment of clinical and pathologic consequences of white matter abnormalities in multiple sclerosis is critical in understanding the pathways of disease. This study aimed to test whether gray matter atrophy was related to abnormalities in connecting white matter and to identify patterns of imaging biomarker abnormalities that were related to patient processing speed.Materials and MethodsImage data and Symbol Digit Modalities Test scores were collected from a cohort of patients with early multiple sclerosis. The Network Modification Tool was used to estimate connectivity irregularities by projecting white matter abnormalities onto connecting gray matter regions. Partial least-squares regression quantified the relationship between imaging biomarkers and processing speed as measured by the Symbol Digit Modalities Test.ResultsAtrophy in deep gray matter structures of the thalami and putamen had moderate and significant correlations with abnormalities in connecting white matter (r = 0.39–0.41, P < .05 corrected). The 2 models of processing speed, 1 for each of the WM imaging biomarkers, had goodness-of-fit (R2) values of 0.42 and 0.30. A measure of the impact of white matter lesions on the connectivity of occipital and parietal areas had significant nonzero regression coefficients.ConclusionsWe concluded that deep gray matter regions may be susceptible to inflammation and/or demyelination in white matter, possibly having a higher sensitivity to remote degeneration, and that lesions affecting visual processing pathways were related to processing speed. The Network Modification Tool may be used to quantify the impact of early white matter abnormalities on both connecting gray matter structures and processing speed.

Profilometry: A new statistical framework for the characterization of white matter pathways, with application to multiple sclerosis

“…For example Henry et al () suggested that the higher lesion density they observed in thalamo‐cortical tracts (compared to the remaining white matter) could explain the thalamic atrophy observed early in the disease. Furthermore, Kuceyeski et al () demonstrated significant correlations between atrophy in subcortical regions (including the thalamus) and abnormalities in connecting white matter in MS, as well as a link between subtle cognitive disability and lesions in white matter connecting to the visual system. In a similar fashion, profilometry could help clarify the relationship between lesions and clinical disability (ambulation and cognitive dysfunction).…”

A two-year study using cerebral gray matter volume to assess the response to fingolimod therapy in multiple sclerosis

“…Cerebral GM atrophy begins very early in the disease course [25,67], even before patients manifest their first MS symptoms [30]. Such atrophy is closely associated with physical disability and neuropsychological dysfunction [14,31,32,40,[68][69][70][71][72][73][74][75][76][77][78]. GM may be less prone to transient volume fluctuations as compared to WM [26,27], providing a more sensitive and specific measure of neurodegeneration than whole brain volume [61].…”

“…Taken together, these results show the ability of DMTs to exert a partial but significant effect on limiting the rate of cerebral GM atrophy. Numerous mechanisms have been proposed regarding the pathophysiology of GM atrophy in patients with MS, including direct formation of demyelinating plaques, microglial proliferation, leptomeningeal inflammation, anti-lipid antibodies, micro-RNAs, oxidative stress, and Wallerian degeneration [27,44,56,57,[62][63][64][65][66]75]. Understanding fingolimod's proposed mechanism of action may provide some explanation as to how this DMT impacts GM atrophy.…”

Structural connectome disruption at baseline predicts 6-months post-stroke outcome

“…The NeMo Tool has recently been used to investigate lesion‐dysfunction relationships [Kuceyeski et al, ] and longitudinal remote degeneration [Kuceyeski et al, ] in stroke. It has also been used to relate white matter and gray matter pathologies in normal aging [Glodzik et al, ] and reveal lesion‐symptom relationships in subtle cognitive impairment associated with early multiple sclerosis [Kuceyeski et al, ]. Two main advantages of the NeMo Tool are that it uses MRI sequences routinely obtained in the acute clinical setting and does not require expertise in advanced diffusion image processing and tractography.…”