Early Multiple Sclerosis Patients Research Articles

Regional hippocampal atrophy reflects memory impairment in patients with early relapsing remitting multiple sclerosis.

Research work has shown that hippocampal subfields are atrophic to varying extents in multiple sclerosis (MS) patients. However, studies examining the functional implications of subfield-specific hippocampal damage in early MS are limited. We aim to gain insights into the relationship between hippocampal atrophy and memory function by investigating the correlation between global and regional hippocampal atrophy and memory performance in early MS patients. From the Italian Neuroimaging Network Initiative (INNI) dataset, we selected 3D-T1-weighted brain MRIs of 219 early relapsing remitting (RR)MS and 246 healthy controls (HC) to identify hippocampal atrophic areas. At the time of MRI, patients underwent Selective-Reminding-Test (SRT) and Spatial-Recall-Test (SPART) and were classified as mildly (MMI-MS: n.110) or severely (SMI-MS: n:109) memory impaired, according to recently proposed cognitive phenotypes. Early RRMS showed lower hippocampal volumes compared to HC (p < 0.001), while these did not differ between MMI-MS and SMI-MS. In MMI-MS, lower hippocampal volumes correlated with worse memory tests (r = 0.23-0.37, p ≤ 0.01). Atrophic voxels were diffuse in the hippocampus but more prevalent in cornu ammonis (CA, 79%) than in tail (21%). In MMI-MS, decreased subfield volumes correlated with decreases in memory, particularly in the right CA1 (SRT-recall: r = 0.38; SPART: r = 0.34, p < 0.01). No correlations were found in the SMI-MS group. Hippocampal atrophy spreads from CA to tail from early disease stages. Subfield hippocampal atrophy is associated with memory impairment in MMI-MS, while this correlation is lost in SMI-MS. This plays in favor of a limited capacity for an adaptive functional reorganization of the hippocampi in MS patients.

Tract-wise microstructural analysis informs on current and future disability in early multiple sclerosis

ObjectivesMicrostructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize microstructural brain tissue changes both in lesions and normal-appearing brain tissue. However, the impact of the location of microstructural alterations in terms of neuronal pathways has not been thoroughly explored so far. Here, we study the extent and the location of tissue changes probed using quantitative MRI along white matter (WM) tracts extracted from a connectivity atlas.MethodsWe quantified voxel-wise T1 tissue alterations compared to normative values in a cohort of 99 MS patients. For each WM tract, we extracted metrics reflecting tissue alterations both in lesions and normal-appearing WM and correlated these with cross-sectional disability and disability evolution after 2 years.ResultsIn early MS patients, T1 alterations in normal-appearing WM correlated better with disability evolution compared to cross-sectional disability. Further, the presence of lesions in supratentorial tracts was more strongly associated with cross-sectional disability, while microstructural alterations in infratentorial pathways yielded higher correlations with disability evolution. In progressive patients, all major WM pathways contributed similarly to explaining disability, and correlations with disability evolution were generally poor.ConclusionsWe showed that microstructural changes evaluated in specific WM pathways contribute to explaining future disability in early MS, hence highlighting the potential of tract-wise analyses in monitoring disease progression. Further, the proposed technique allows to estimate WM tract-specific microstructural characteristics in clinically compatible acquisition times, without the need for advanced diffusion imaging.

Identification of multiple sclerosis endophenotypes by high dimensional blood signatures associated with distinct disease trajectories (P1-3.008)

Identification of multiple sclerosis endophenotypes by high dimensional blood signatures associated with distinct disease trajectories (P1-3.008)

Lesion location across diagnostic regions in multiple sclerosis

BackgroundLesions in the periventricular, (juxta)cortical, and infratentorial region, as visible on brain MRI, are part of the diagnostic criteria for Multiple sclerosis (MS) whereas lesions in the subcortical region are currently only a marker of disease activity. It is unknown whether MS lesions follow individual spatial patterns or whether they occur in a random manner across diagnostic regions. AimFirst, to describe cross-sectionally the spatial lesion patterns in patients with MS. Second, to investigate the spatial association of new lesions and lesions at baseline across diagnostic regions. MethodsExperienced neuroradiologists analyzed brain MRI (3D, 3T) in a cohort of 330 early MS patients. Lesions at baseline and new solitary lesions after two years were segmented (manually and by consensus) and classified as periventricular, (juxta)cortical, or infratentorial (diagnostic regions) or subcortical—with or without Gadolinium-enhancement. Gadolinium enhancement of lesions in the different regions was compared by Chi square test. New lesions in the four regions served as dependent variable in four zero-inflated Poisson models each with the six independent variables of lesions in the four regions at baseline, age and gender. ResultsAt baseline, lesions were most often observed in the subcortical region (mean 13.0 lesions/patient), while lesion volume was highest in the periventricular region (mean 2287 µl/patient). Subcortical lesions were less likely to show gadolinium enhancement (3.1 %) than juxtacortical (4.3 %), periventricular (5.3 %) or infratentorial lesions (7.2 %). Age was inversely correlated with new periventricular, juxtacortical and subcortical lesions. New lesions in the periventricular, juxtacortical and infratentorial region showed a significant autocorrelative behavior being positively related to the number of lesions in the respective regions at baseline. New lesions in the subcortical region showed a different behavior with a positive association with baseline periventricular lesions and a negative association with baseline infratentorial lesions. ConclusionAcross regions, new lesions do not occur randomly; instead, new lesions in the periventricular, juxtacortical and infratentorial diagnostic region are associated with that at baseline. Lesions in the subcortical regions are more closely related to periventricular lesions. Moreover, subcortical lesions substantially contribute to lesion burden in MS but are less likely to show gadolinium enhancement (than lesions in the diagnostic regions).

Task-based functional MRI challenges in clinical neuroscience: Choice of the best head motion correction approach in multiple sclerosis.

Functional MRI (fMRI) is commonly used for understanding brain organization and connectivity abnormalities in neurological conditions, and in particular in multiple sclerosis (MS). However, head motion degrades fMRI data quality and influences all image-derived metrics. Persistent controversies regarding the best correction strategy motivates a systematic comparison, including methods such as scrubbing and volume interpolation, to find optimal correction models, particularly in studies with clinical populations prone to characterize by high motion. Moreover, strategies for correction of motion effects gain more relevance in task-based designs, which are less explored compared to resting-state, have usually lower sample sizes, and may have a crucial role in describing the functioning of the brain and highlighting specific connectivity changes. We acquired fMRI data from 17 early MS patients and 14 matched healthy controls (HC) during performance of a visual task, characterized motion in both groups, and quantitatively compared the most used and easy to implement methods for correction of motion effects. We compared task-activation metrics obtained from: (i) models containing 6 or 24 motion parameters (MPs) as nuisance regressors; (ii) models containing nuisance regressors for 6 or 24 MPs and motion outliers (scrubbing) detected with Framewise Displacement or Derivative or root mean square VARiance over voxelS; and (iii) models with 6 or 24 MPs and motion outliers corrected through volume interpolation. To our knowledge, volume interpolation has not been systematically compared with scrubbing, nor investigated in task fMRI clinical studies in MS. No differences in motion were found between groups, suggesting that recently diagnosed MS patients may not present problematic motion. In general, models with 6 MPs perform better than models with 24 MPs, suggesting the 6 MPs as the best trade-off between correction of motion effects and preservation of valuable information. Parsimonious models with 6 MPs and volume interpolation were the best combination for correcting motion in both groups, surpassing the scrubbing methods. A joint analysis regardless of the group further highlighted the value of volume interpolation. Volume interpolation of motion outliers is an easy to implement technique, which may be an alternative to other methods and may improve the accuracy of fMRI analyses, crucially in clinical studies in MS and other neurological populations.

Improved prediction of early cognitive impairment in multiple sclerosis combining blood and imaging biomarkers.

Disability in multiple sclerosis is generally classified by sensory and motor symptoms, yet cognitive impairment has been identified as a frequent manifestation already in the early disease stages. Imaging- and more recently blood-based biomarkers have become increasingly important for understanding cognitive decline associated with multiple sclerosis. Thus, we sought to determine the prognostic utility of serum neurofilament light chain levels alone and in combination with MRI markers by examining their ability to predict cognitive impairment in early multiple sclerosis. A comprehensive and detailed assessment of 152 early multiple sclerosis patients (Expanded Disability Status Scale: 1.3 ± 1.2, mean age: 33.0 ± 10.0 years) was performed, which included serum neurofilament light chain measurement, MRI markers (i.e. T2-hyperintense lesion volume and grey matter volume) acquisition and completion of a set of cognitive tests (Symbol Digits Modalities Test, Paced Auditory Serial Addition Test, Verbal Learning and Memory Test) and mood questionnaires (Hospital Anxiety and Depression scale, Fatigue Scale for Motor and Cognitive Functions). Support vector regression, a branch of unsupervised machine learning, was applied to test serum neurofilament light chain and combination models of biomarkers for the prediction of neuropsychological test performance. The support vector regression results were validated in a replication cohort of 101 early multiple sclerosis patients (Expanded Disability Status Scale: 1.1 ± 1.2, mean age: 34.4 ± 10.6 years). Higher serum neurofilament light chain levels were associated with worse Symbol Digits Modalities Test scores after adjusting for age, sex Expanded Disability Status Scale, disease duration and disease-modifying therapy (B = −0.561; SE = 0.192; P = 0.004; 95% CI = −0.940 to −0.182). Besides this association, serum neurofilament light chain levels were not linked to any other cognitive or mood measures (all P-values > 0.05). The tripartite combination of serum neurofilament light chain levels, lesion volume and grey matter volume showed a cross-validated accuracy of 88.7% (90.8% in the replication cohort) in predicting Symbol Digits Modalities Test performance in the support vector regression approach, and outperformed each single biomarker (accuracy range: 68.6–75.6% and 68.9–77.8% in the replication cohort), as well as the dual biomarker combinations (accuracy range: 71.8–82.3% and 72.6–85.6% in the replication cohort). Taken together, early neuro-axonal loss reflects worse information processing speed, the key deficit underlying cognitive dysfunction in multiple sclerosis. Our findings demonstrate that combining blood and imaging measures improves the accuracy of predicting cognitive impairment, highlighting the clinical utility of cross-modal biomarkers in multiple sclerosis.

The central vein sign helps in differentiating multiple sclerosis from its mimickers: lessons from Fabry disease.

Although the use of specific MRI criteria has significantly increased the diagnostic accuracy of multiple sclerosis (MS), reaching a correct neuroradiological diagnosis remains a challenging task, and therefore the search for new imaging biomarkers is crucial. This study aims to evaluate the incidence of one of the emerging neuroradiological signs highly suggestive of MS, the central vein sign (CVS), using data from Fabry disease (FD) patients as an index of microvascular disorder that could mimic MS. In this retrospective study, after the application of inclusion and exclusion criteria, MRI scans of 36 FD patients and 73 relapsing-remitting (RR) MS patients were evaluated. Among the RRMS participants, 32 subjects with a disease duration inferior to 5years (early MS) were also analyzed. For all subjects, a Fazekas score (FS) was recorded, excluding patients with FS = 0. Different neuroradiological signs, including CVS, were evaluated on FLAIR T2-weighted and spoiled gradient recalled echo sequences. Among all the recorded neuroradiological signs, the most striking difference was found for the CVS, with a detectable prevalence of 78.1% (57/73) in RRMS and of 71.4% (25/32) in early MS patients, while this sign was absent in FD (0/36). Our results confirm the high incidence of CVS in MS, also in the early phases of the disease, while it seems to be absent in conditions with a different etiology. These results corroborate the possible role of CVS as a useful neuroradiological sign highly suggestive of MS. • The search for new imaging biomarkers is crucial to achieve a correct neuroradiological diagnosis of MS. • The CVS shows an incidence superior to 70% in MS patients, even in the early phases of the disease, while it appears to be absent in FD. • These findings further corroborate the possible future central role of CVS in distinguishing between MS and its mimickers.

Periventricular gradient of T1 tissue alterations in multiple sclerosis

ObjectivePathology in multiple sclerosis is not homogenously distributed. Recently, it has been shown that structures adjacent to CSF are more severely affected. A gradient of brain tissue involvement was shown with more severe pathology in periventricular areas and in proximity to brain surfaces such as the subarachnoid spaces and ependyma, and hence termed the “surface–in” gradient. Here, we study whether (i) the surface-in gradient of periventricular tissue alteration measured by T1 relaxometry is already present in early multiple sclerosis patients, (ii) how it differs between early and progressive multiple sclerosis patients, and (iii) whether the gradient-derived metrics in normal-appearing white matter and lesions correlate better with physical disability than conventional MRI-based metrics. MethodsForty-seven patients with early multiple sclerosis, 52 with progressive multiple sclerosis, and 92 healthy controls were included in the study. Isotropic 3D T1 relaxometry maps were obtained using the Magnetization-Prepared 2 Rapid Acquisition Gradient Echoes sequence at 3 T. After spatially normalizing the T1 maps into a study-specific common space, T1 inter-subject variability within the healthy cohort was modelled voxel-wise, yielding a normative T1 atlas. Individual comparisons of each multiple sclerosis patient against the atlas were performed by computing z-scores. Equidistant bands of voxels were defined around the ventricles in the supratentorial white matter; the z-scores in these bands were analysed and compared between the early and progressive multiple sclerosis cohorts. Correlations between both conventional and z-score-gradient-derived MRI metrics and the Expanded Disability Status Scale were assessed. ResultsPatients with early and progressive multiple sclerosis demonstrated a periventricular gradient of T1 relaxation time z-scores. In progressive multiple sclerosis, z-score-derived metrics reflecting the gradient of tissue abnormality in normal-appearing white matter were more strongly correlated with disability (maximal rho = 0.374) than the conventional lesion volume and count (maximal rho = 0.189 and 0.21 respectively). In early multiple sclerosis, the gradient of normal-appearing white matter volume with z-scores > 2 at baseline correlated with clinical disability assessed at two years follow-up. ConclusionOur results suggest that the surface-in white matter gradient of tissue alteration is detectable with T1 relaxometry and is already present at clinical disease onset. The periventricular gradients correlate with clinical disability. The periventricular gradient in normal-appearing white matter may thus qualify as a promising biomarker for monitoring of disease activity from an early stage in all phenotypes of multiple sclerosis.

Corpus callosum volumetrics and clinical progression in early multiple sclerosis.

Corpus callosum (CC) is commonly affected in multiple sclerosis (MS), with known association between CC atrophy and MS clinical activity. In this study, we assessed the association of callosal atrophy, lesions volume and residual CC volume with the clinical disability of early MS patients. Thirteen MS subjects (9 female, mean age 36.9 years), studied with magnetic resonance imaging (MRI) were selected. MRI scans were performed at baseline (T0), at 6 (T1), 12 (T2), and 24 months (T3) from baseline. CC was segmented into three sections (genu, body, and splenium); callosal boundaries were outlined and all CC lesions were manually traced. Normal CC and CC lesion volumes were measured using a semiautomatic software. From January 2014 to December 2016, all selected patients had confluent lesions on MRI at T3 with a significant increase in the size of confluent lesions compared to baseline (p=0.0007). At T1, a significant increase in the size of confluent (p=0.02) and single lesions located in the callosal body (p=0.04) was detected in patients with EDSS ≥1.5. Also, CC residual volume (CCR) rather than the whole CC volume (CCV) significantly correlated (p=0.03) with the clinical progression of MS in the whole cohort. In early MS patients with higher EDSS at baseline, a significant increase in confluent CC lesions size is evident, particularly in the callosal body. Also, median CCR is significantly associated with MS progression in the whole MS group, regardless of initial EDSS. Given their significant association with disability, we encourage measuring CC body lesions and residual CC size for therapeutic decisions and prognostic planning in early MS.

Quantification of normal-appearing white matter damage in early relapse-onset multiple sclerosis through neurite orientation dispersion and density imaging

Background Neurodegeneration is a major contributor of neurological disability in multiple sclerosis (MS). The possibility to fully characterize normal appearing white matter (NAWM) damage could provide the missing information needed to clarify the mechanisms beyond disability accumulation.Objective In the present study we aimed to characterize the presence and extent of NAWM damage and its correlation with clinical disability.Methods We applied Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) in a cohort of 27 early relapse-onset MS patients (disease duration < 5 years) compared to a population of 26 age- and sex-matched healthy controls (HCs). All patients underwent a neurological examination, including the Expanded Disability Status Scale (EDSS).Results MS patients showed lower fractional anisotropy (FA) and higher mean diffusivity (MD) values in the main WM bundles, such as the corticospinal tract, corpus callosum, superior and middle cerebellar peduncles, posterior thalamic radiation (which includes optic radiation), cingulum and external capsule. All brain areas with reduced FA/increased MD also displayed a reduction in neurite density index (NDI). However, comparing individual voxels of the WM skeleton between MS and HCs, a higher number of NDI significant voxels was disclosed compared to FA/MD (56.4% vs 11.2%/41.2%). No significant correlations were observed between DTI/NODDI metrics and EDSS.Conclusions Our findings suggest that NDI may allow for a better characterization and understanding of the microstructural changes in the NAWM since the early relapsing-remitting MS phases. Future longitudinal studies including a larger cohort of patients with different clinical phenotypes may clarify the association between NODDI metrics and disability progression.

Progression independent of relapse activity in early multiple sclerosis patients

Disability accrual in multiple sclerosis (MS) may occur as relapse-associated worsening (RAW) or progression independent of relapse activity (PIRA). We investigated the contribution of RAW and PIRA to confirmed disability accumulation (CDA) in patients with clinically isolated syndrome (CIS) and early relapsing-remitting (RR) MS.

Machine learning to investigate superficial white matter integrity in early multiple sclerosis.

This study aims todetermine the sensitivity of superficial white matter (SWM) integrity as a metric to distinguish early multiple sclerosis (MS) patients from healthy controls (HC). Fractional anisotropy and mean diffusivity (MD) values from SWM bundles across the cortex and major deep white matter (DWM) tracts were extracted from 29 early MS patients and 31 age- and sex-matched HC. Thickness of 68 cortical regions and resting-state functional-connectivity (RSFC) among them were calculated. The distribution of structural and functional metrics between groups were compared using Wilcoxon rank-sum test. Utilizing a machine learning method (adaptive boosting), 6 models were built based on: 1-SWM, 2-DWM, 3-SWM and DWM, 4-cortical thickness, or 5-RSFC measures. In model 6, all features from previous models were incorporated. The models were trained with nested 5-folds cross-validation. Area under the receiver operating characteristic curve (AUCroc ) values were calculated to evaluate classification performance of each model. Permutation tests were used to compare the AUCroc values. Patients had higher MD in SWM bundles including insula, inferior frontal, orbitofrontal, superior and medial temporal, and pre- and post-central cortices (p < .05). No group differences were found for any other MRI metric. The model incorporating SWM and DWM features provided the best classification (AUCroc = 0.75). The SWM model provided higher AUCroc (0.74), compared to DWM (0.63), cortical thickness (0.67), RSFC (0.63), and all-features (0.68) models (p < .001 for all). Our results reveal a non-random pattern of SWM abnormalities at early stages of MS even before pronounced structural and functional alterations emerge.

Mass Cytometry Identifies Expansion of T-bet+ B Cells and CD206+ Monocytes in Early Multiple Sclerosis.

Multiple sclerosis (MS) is an immune-driven demyelinating disease of the central nervous system. Immune cell features are particularly promising as predictive biomarkers due to their central role in the pathogenesis but also as drug targets, even if nowadays, they have no impact in clinical practice. Recently, high-resolution approaches, such as mass cytometry (CyTOF), helped to better understand the diversity and functions of the immune system. In this study, we performed an exploratory analysis of blood immune response profiles in healthy controls and MS patients sampled at their first neurological relapse, using two large CyTOF panels including 62 markers exploring myeloid and lymphoid cells. An increased abundance of both a T-bet-expressing B cell subset and a CD206+ classical monocyte subset was detected in the blood of early MS patients. Moreover, T-bet-expressing B cells tended to be enriched in aggressive MS patients. This study provides new insights into understanding the pathophysiology of MS and the identification of immunological biomarkers. Further studies will be required to validate these results and to determine the exact role of the identified clusters in neuroinflammation.

Serum neurofilament levels reflect outer retinal layer changes in multiple sclerosis.

Background:Serum neurofilament light chain (sNfL) and distinct intra-retinal layers are both promising biomarkers of neuro-axonal injury in multiple sclerosis (MS). We aimed to unravel the association of both markers in early MS, having identified that neurofilament has a distinct immunohistochemical expression pattern among intra-retinal layers.Methods:Three-dimensional (3D) spectral domain macular optical coherence tomography scans and sNfL levels were investigated in 156 early MS patients (female/male: 109/47, mean age: 33.3 ± 9.5 years, mean disease duration: 2.0 ± 3.3 years). Out of the whole cohort, 110 patients had no history of optic neuritis (NHON) and 46 patients had a previous history of optic neuritis (HON). In addition, a subgroup of patients (n = 38) was studied longitudinally over 2 years. Support vector machine analysis was applied to test a regression model for significant changes.Results:In our cohort, HON patients had a thinner outer plexiform layer (OPL) volume compared to NHON patients (B = −0.016, SE = 0.006, p = 0.013). Higher sNfL levels were significantly associated with thinner OPL volumes in HON patients (B = −6.734, SE = 2.514, p = 0.011). This finding was corroborated in the longitudinal subanalysis by the association of higher sNfL levels with OPL atrophy (B = 5.974, SE = 2.420, p = 0.019). sNfL levels were 75.7% accurate at predicting OPL volume in the supervised machine learning.Conclusions:In summary, sNfL levels were a good predictor of future outer retinal thinning in MS. Changes within the neurofilament-rich OPL could be considered as an additional retinal marker linked to MS neurodegeneration.

Classifying multiple sclerosis patients on the basis of SDMT performance using machine learning

Objective: To build a model to predict cognitive status reflecting structural, functional, and white matter integrity changes in early multiple sclerosis (MS). Methods: Based on Symbol Digit Modalities Test (SDMT) performance, 183 early MS patients were assigned “lower” or “higher” performance groups. Three-dimensional (3D)-T2, T1, diffusion weighted, and resting-state magnetic resonance imaging (MRI) data were acquired in 3T. Using Random Forest, five models were trained to classify patients into two groups based on 1—demographic/clinical, 2—lesion volume/location, 3—local/global tissue volume, 4—local/global diffusion tensor imaging, and 5—whole-brain resting-state-functional-connectivity measures. In a final model, all important features from previous models were concatenated. Area under the receiver operating characteristic curve (AUC) values were calculated to evaluate classifier performance. Results: The highest AUC value (0.90) was achieved by concatenating all important features from neuroimaging models. The top 10 contributing variables included volumes of bilateral nucleus accumbens and right thalamus, mean diffusivity of left cingulum-angular bundle, and functional connectivity among hubs of seven large-scale networks. Conclusion: These results provide an indication of a non-random brain pattern mostly compromising areas involved in attentional processes specific to patients who perform worse in SDMT. High accuracy of the final model supports this pattern as a potential neuroimaging biomarker of subtle cognitive changes in early MS.

Immune signatures of prodromal multiple sclerosis in monozygotic twins.

The tremendous heterogeneity of the human population presents a major obstacle in understanding how autoimmune diseases like multiple sclerosis (MS) contribute to variations in human peripheral immune signatures. To minimize heterogeneity, we made use of a unique cohort of 43 monozygotic twin pairs clinically discordant for MS and searched for disease-related peripheral immune signatures in a systems biology approach covering a broad range of adaptive and innate immune populations on the protein level. Despite disease discordance, the immune signatures of MS-affected and unaffected cotwins were remarkably similar. Twinship alone contributed 56% of the immune variation, whereas MS explained 1 to 2% of the immune variance. Notably, distinct traits in CD4+ effector T cell subsets emerged when we focused on a subgroup of twins with signs of subclinical, prodromal MS in the clinically healthy cotwin. Some of these early-disease immune traits were confirmed in a second independent cohort of untreated early relapsing-remitting MS patients. Early involvement of effector T cell subsets thus points to a key role of T cells in MS disease initiation.

Lipoprotein profiling in early multiple sclerosis patients: effect of chronic inflammation?

BackgroundInflammatory cytokines contribute to proatherogenic changes in lipid metabolism by reduction of HDL-cholesterol (HDL-C) levels, impairment of its antiinflammatory and antioxidant functions. Therefore, the protective actions of HDL-C can be limited in chronic inflammatory diseases such as multiple sclerosis (MS). The aim of this study was to assess the association between lipoprotein subfractions and inflammatory status in early stages of multiple sclerosis.MethodsPolyacrylamide gel electrophoresis Lipoprint© System was used for lipoprotein profile analysis in 19 newly diagnosed MS patients, and in matched 19 healthy controls. Serum levels of interleukin (IL) 1β, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12 (p70), IL-13, IL-17, granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor, interferon-γ and TNF-α were measured by multiplex bead assay.ResultsConcentrations of the measured cytokines and lipoprotein subclasses were comparable between MS patients and controls. Male, but not female MS patients had significantly higher total HDL-C and small HDL-C subfraction than healthy controls. Large HDL-C negatively correlated with all measured cytokines except IL-17 in MS but not in controls. Intermediate HDL-C subfractions correlated positively with all measured cytokines except G-CSF in MS females but not in MS males or controls.ConclusionOur results of higher HDL-C and mainly its small HDL-C subfraction suggest that male MS patients are at higher risk of atherosclerosis and the subtle dyslipidemia is present in early stages of the disease. The correlations between specific HDL-C subfractions and the inflammatory cytokines demonstrate mutual links between systemic inflammation and lipid metabolism in MS.Trial registrationClinicalTrials.gov, Identifier: NCT 03052595 Registered on Feb 14, 2017.

Developmental Venous Anomalies are More Common in Patients with Multiple Sclerosis and Clinically Isolated Syndrome : Coincidence or Relevant?

Developmental venous anomalies (DVA) are congenital malformations of veins that drain brain parenchyma, with a prevalence up to 9.3% in normal populations and 29.5% in multiple sclerosis (MS) patients. Study purpose was to determine prevalence of DVAs in patients with clinically isolated syndrome (CIS) and early relapsing-remitting multiple sclerosis (RRMS) and to assess whether DVAs are related to altered clinical, magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) laboratory parameters. Routine neurological and MRI examinations took place in asingle center in 93 patients (39 CIS, 54 RRMS). Clinical disability (n = 93), MRI (n ≤ 90), CSF (n ≤ 82) parameters and DVA status were determined and compared statistically. A total of 29DVAs were detected in 25patients (25/93; 26.9%), 10 in 39CIS patients and 15 in 54RRMS patients. Most parameters were not significantly altered in patients with DVAs; no associated higher conversion rates from CIS to MS at 1-year (p = 0.411) or 2‑year follow-up (p = 0.281) were registered. A higher prevalence of DVAs was detected in CIS and early MS patients than reported in non-MS populations, congruent to recent literature. The DVAs were not associated with significantly altered clinical outcomes, brain atrophy rates or disease progression, and no associated higher risk of CIS patients for converting to MS was found.

Word-finding difficulty is a prevalent disease-related deficit in early multiple sclerosis

Background: Persons with multiple sclerosis (MS) commonly report word-finding difficulty clinically, yet this language deficit remains underexplored. Objective: To investigate the prevalence and nature of word-finding difficulty in persons with early MS on three levels: patient report, cognitive substrates, and neuroimaging. Methods: Two samples of early MS patients (n = 185 and n = 55; ⩽5 years diagnosed) and healthy controls (n = 50) reported frequency/severity of cognitive deficits and underwent objective assessment with tasks of rapid automatized naming (RAN), measuring lexical access speed, memory, word generation, and cognitive efficiency. High-resolution brain magnetic resonance imaging (MRI) derived measurements of regional cortical thickness, global and deep gray matter volume, and T2 lesion volume. Relationships among patient-reported word-finding difficulty, cognitive performance, and neural correlates were examined. Results: Word-finding difficulty was the most common cognitive complaint of MS patients and the only complaint reported more by patients than healthy controls. Only RAN performance discriminated MS patients with subjective word-finding deficits from those without subjective complaints and from healthy controls. Thinner left parietal cortical gray matter independently predicted impaired RAN performance, driven primarily by the left precuneus. Conclusion: Three levels of evidence (patient-report, objective behavior, regional gray matter) support word-finding difficulty as a prevalent, measurable, disease-related deficit in early MS linked to left parietal cortical thinning.

Prognostic value of white matter lesion shrinking in early multiple sclerosis: An intuitive or naïve notion?

Background and purposeNew or enlarging T2‐hyperintense white matter lesions (WML) are associated with clinical disease progression in multiple sclerosis (MS). The prognostic value of WML shrinking is unclear. Assuming that waning of acute inflammation and repair processes would be the main drivers of WML shrinking, we aimed to assess the prognostic value of WML shrinking in early MS.MethodsWe retrospectively analyzed a cohort of 144 early MS patients with three brain MRI scans at baseline and after 1 and 3 years available. All patients were therapy naïve at baseline and 70.5% of them treated with disease modifying drugs at year 1. We determined the volume of WML shrinking between MRI scans, total WML volumes, number of gadolinium‐enhancing and new WML, white matter (WM) and gray matter volumes at each MRI scan. Clinical disability was measured by Expanded Disability Status Scale. We performed the correlation analyses of WML shrinking with other MRI parameters and clinical outcome.ResultsWhite matter lesions shrinking was highly variable between patients and correlated with the initial number of gadolinium‐enhancing WML and with WM volume decrease. WML shrinking was not associated with clinical outcome.ConclusionWe found no indication of a prognostic value of WML shrinking in early MS patients. WML shrinking seems to be related to waning of acute inflammation.