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Do Cerebral Small Vessel Disease and Multiple Sclerosis Share Common Mechanisms of White Matter Injury?

ABSTRACT: Background and Purpose- The role of inflammation in ischemic white matter disease is increasingly recognized, and further understanding of the pathophysiology might inform future treatment strategies. Multiple sclerosis (MS) is a chronic autoimmune condition in which inflammation plays a central role that also affects the white matter. We hypothesized that white matter injury might share common mechanisms and used statistical genetics techniques to assess whether having genetically elevated white matter hyperintensity (WMH) volume was associated with increased MS risk. Methods- We investigated the genetic association in 2 cohorts with magnetic resonance imaging-quantified ischemic white matter lesion volume (WMH in stroke; n=2797 and UK Biobank; n=8353) and 14?802 cases of MS and 26?703 controls from the International Multiple Sclerosis Genetics Consortium. We further performed individual-level polygenic risk score calculations for MS and measures of structural white matter disease in UK Biobank. Finally, we looked for evidence of overlapping risk across the whole genome. Results- There was no association of genetic variants influencing MS with WMH volume using summary statistics in the WMH in stroke cohort (relative risk score =1.014; 95% CI, 0.936-1.110) or in the UK Biobank cohort (relative risk score =1.030; 95% CI, 0.932-1.117). Conversely, assessing the contribution of single nucleotide polymorphisms significantly associated with WMH on the risk of MS there was no significant association (relative risk score =0.930; 95% CI, 0.736-1.191). There were no significant associations between polygenic risk scores calculations; these results were robust to the selection of single nucleotide polymorphisms at a range of significance thresholds. Whole genome analysis did not reveal any overlap of risk between the traits. Conclusions- Our results do not provide evidence to suggest a shared mechanism of white matter damage in ischemia and MS. We propose that inflammation acts in distinct pathways because of the differing nature of the primary insult.

SUBMITTER: Brown RB

PROVIDER: S-EPMC6661245 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Do Cerebral Small Vessel Disease and Multiple Sclerosis Share Common Mechanisms of White Matter Injury?

Brown Robin B RB Traylor Matthew M Burgess Stephen S Sawcer Stephen S Markus Hugh S HS

Stroke 20190621 8

Background and Purpose- The role of inflammation in ischemic white matter disease is increasingly recognized, and further understanding of the pathophysiology might inform future treatment strategies. Multiple sclerosis (MS) is a chronic autoimmune condition in which inflammation plays a central role that also affects the white matter. We hypothesized that white matter injury might share common mechanisms and used statistical genetics techniques to assess whether having genetically elevated whit ...[more]

PMID: 31221055

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Project description:IntroductionWe have demonstrated that asymptomatic cerebral small vessel disease (cSVD) measured by white matter hyperintensity volume is associated with reduced manipulative manual dexterity on the Grooved Peg Board Test (GPBT) in middle-aged healthy individuals with a family history of early coronary artery disease. In this current study, we aim to identify the association of subcortical white matter microstructural impairment measured by diffusion tensor imaging, manual dexterity measured by GPBT and circulating serums ceramide, another marker for white matter injury. We hypothesize that lower regional fractional anisotropy (rFA) is associated with worse performance on GPBT and elevated serum ceramides in the same study population.MethodsrFA of 48 regions representing the subcortical white matters were analyzed in GeneSTAR participants in addition to serum ceramides and GPBT scores. Unadjusted univariable analyses with Bonferroni correction for multiple comparisons were completed using Spearman correlation for testing the associations between ceramides, rFA of subcortical white matter, and GPBT performance. Subsequently, sensitivity analyses were performed after excluding the participants that had any physical limitation that may influence their performance on GPBT. Finally, in the adjusted analysis using generalized estimating equation, linear regression models were performed for the areas that met significance threshold in the unadjusted analyses.Results112 subjects (age [49 ± 11], 51% female, 39.3% African American) were included. Adjusted analyses for the significant correlations that met the Bonferroni correction threshold in the unadjusted univariable analyses identified significant negative associations between rFA of the right fornix (RF) and log-GPBT score (β = -0.497, p = 0.037). In addition, rFA of RF negatively correlated with log serum ceramide levels (C18: β = -0.03, p = 0.003, C20: β = -0.0002, p = 0.004) and rFA of left genu of corpus callosum negatively correlated with log C18 level (β = -0.0103, p = 0.027).ConclusionsThese results demonstrate that subcortical microstructural white matter disruption is associated with elevated serum ceramides and reduced manual dexterity in a population with cSVD. These findings suggest that injury to white matter tracts undermines neural networks, with functional consequences in a middle-aged population with cardiovascular risk factors.

Project description:Objective: Reliable quantification of white matter hyperintensities (WHMs) resulting from cerebral small vessel diseases (CSVD) is essential for understanding their clinical impact. We aim to develop and clinically validate a deep learning system for automatic segmentation of CSVD-WMH from fluid-attenuated inversion recovery (FLAIR) imaging using large multicenter data. Method: A FLAIR imaging dataset of 1,156 patients diagnosed with CSVD associated WMH (median age, 54 years; 653 males) obtained between September 2018 and September 2019 from Beijing Tiantan Hospital was retrospectively analyzed in this study. Locations of CSVD-WMH on the FLAIR scans were manually marked by two experienced neurologists. Using the manually labeled data of 996 patients (development set), a U-shaped novel 2D convolutional neural network (CNN) architecture was trained for automatic segmentation of CSVD-WMH. The segmentation performance of the network was evaluated with per pixel and lesion level dice scores using an independent internal test set (n = 160) and a multi-center external test set (n = 90, three medical centers). The clinical suitability of the segmentation results, classified as acceptable, acceptable with minor revision, acceptable with major revision, and not acceptable, was analyzed by three independent neuroradiologists. The inter-neuroradiologists agreement rate was assessed by the Kendall-W test. Results: On the internal and external test sets, the proposed CNN architecture achieved per pixel and lesion level dice scores of 0.72 (external test set), and they were significantly better than the state-of-the-art deep learning architectures proposed for WMH segmentation. In the clinical evaluation, neuroradiologists observed the segmentation results for 95% of the patients were acceptable or acceptable with a minor revision. Conclusions: A deep learning system can be used for automated, objective, and clinically meaningful segmentation of CSVD-WMH with high accuracy.

Project description:To explore the correlation between the number of lenticulostriate arteries (LSAs) and the white matter features in cerebral small vessel diseases (CSVD) by 3T magnetic resonance imaging (MRI). Seventy-one patients with diagnoses of CSVD were prospectively enrolled to undergo 3T MRI examination, including high-resolution vascular wall imaging (VWI) and diffusion tensor imaging (DTI). The LSAs were observed and counted on VWI, and the patients were divided into three groups according to the LSA counts. The presence of white matter hyperintensities (WMHs), lacunes, cerebral microbleeds (CMBs), and enlarged perivascular spaces (EPVS) was assessed in each patient, and a composite CSVD score was calculated. Periventricular and deep white matter hyperintensity (PVWMH, DWMH) volume ratios were obtained based on automatic segmentation. Fractional anisotropy (FA) and mean diffusivity (MD) were processed by using tract-based spatial statistics (TBSS) analysis. These parameters were compared among the three groups. Correlations between the LSA counts and white matter features were also analyzed. There were differences in WMHs (P = 0.001), CMBs (P < 0.001), EPVS (P = 0.017), composite CSVD scores (P < 0.001), PVWMH volume ratios (P = 0.001), DWMH volume ratios (P < 0.001), global FA (P = 0.001), and global MD (P = 0.002) among the three groups. There were correlations between the LSA counts and WMHs (r = -0.45, P < 0.001), CMBs (r = -0.44, P < 0.001), EPVS (r = -0.28, P = 0.020), the composite CSVD score (r = -0.52, P < 0.001), DWMH volume ratio (r = -0.47, P < 0.001), PWMH volume ratio (r = -0.34, P = 0.004), global FA (r = 0.36, P = 0.002), and global MD (r = -0.33, P = 0.005). Diabetes mellitus (OR 3.36, 95% CI 1.06-10.63; P = 0.039) and increased DWMH volume ratios (OR 1.04, 95% CI 1.00-1.08; P = 0.048) were independent risk factors for a decrease in LSA counts. TBSS analysis showed differences among the three groups in global FA and MD after adjusting for age and sex (P < 0.05). The LSA counts was associated with white matter microstructure changes in CSVD and has the potential to represent the extent of subcortical microvascular damage in CSVD patients.

Dataset Information

Do Cerebral Small Vessel Disease and Multiple Sclerosis Share Common Mechanisms of White Matter Injury?

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Do Cerebral Small Vessel Disease and Multiple Sclerosis Share Common Mechanisms of White Matter Injury?

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