No abstract

Background: We aim to evaluate serum neurofilament light chain (sNfL), indicating neuroaxonal damage, as a biomarker at diagnosis in a large cohort of early multiple sclerosis (MS) patients. Methods: In a multicentre prospective longitudinal observational cohort, patients with newly diagnosed relapsing-remitting MS (RRMS) or clinically isolated syndrome (CIS) were recruited between August 2010 and November 2015 in 22 centers. Clinical parameters, MRI, and sNfL levels (measured by single molecule array) were assessed at baseline and up to four-year follow-up. Findings: Of 814 patients, 54.7% (445) were diagnosed with RRMS and 45.3% (369) with CIS when applying 2010 McDonald criteria (RRMS[2010] and CIS[2010]). After reclassification of CIS [2010] patients with existing CSF analysis, according to 2017 criteria, sNfL levels were lower in CIS[2017] than RRMS[2017] patients (9.1 pg/ml, IQR 6.2À13.7 pg/ml, n = 45; 10.8 pg/ml, IQR 7.4À20.1 pg/ml, n = 213; p = 0.036

Neuroinflammation is a pathophysiological hallmark of multiple sclerosis and has a close mechanistic link to neurodegeneration. Although this link is potentially targetable, robust translatable models to reliably quantify and track neuroinflammation in both mice and humans are lacking. The choroid plexus (ChP) plays a pivotal role in regulating the trafficking of immune cells from the brain parenchyma into the cerebrospinal fluid (CSF) and has recently attracted attention as a key structure in the initiation of inflammatory brain responses. In a translational framework, we here address the integrity and multidimensional characteristics of the ChP under inflammatory conditions and question whether ChP volumes could act as an interspecies marker of neuroinflammation that closely interrelates with functional impairment. Therefore, we explore ChP characteristics in neuroinflammation in patients with multiple sclerosis and in two experimental mouse models, cuprizone diet-related demyelination and experimental autoimmune encephalomyelitis. We demonstrate that ChP enlargement—reconstructed from MRI—is highly associated with acute disease activity, both in the studied mouse models and in humans. A close dependency of ChP integrity and molecular signatures of neuroinflammation is shown in the performed transcriptomic analyses. Moreover, pharmacological modulation of the blood–CSF barrier with natalizumab prevents an increase of the ChP volume. ChP enlargement is strongly linked to emerging functional impairment as depicted in the mouse models and in multiple sclerosis patients. Our findings identify ChP characteristics as robust and translatable hallmarks of acute and ongoing neuroinflammatory activity in mice and humans that could serve as a promising interspecies marker for translational and reverse-translational approaches.

Our findings suggest that network functionality in MS is maintained through structural adaptation towards increased local and modular connectivity, patterns linked to adaptability and homeostasis.

Focal demyelinated lesions, diffuse white matter (WM) damage, and gray matter (GM) atrophy influence directly the disease progression in patients with multiple sclerosis. The aim of this study was to identify specific characteristics of GM and WM structural networks in subjects with clinically isolated syndrome (CIS) in comparison to patients with early relapsing-remitting multiple sclerosis (RRMS). Twenty patients with CIS, 33 with RRMS, and 40 healthy subjects were investigated using 3 T-MRI. Diffusion tensor imaging was applied, together with probabilistic tractography and fractional anisotropy (FA) maps for WM and cortical thickness correlation analysis for GM, to determine the structural connectivity patterns. A network topology analysis with the aid of graph theoretical approaches was used to characterize the network at different community levels (modularity, clustering coefficient, global, and local efficiencies). Finally, we applied support vector machines (SVM) to automatically discriminate the two groups. In comparison to CIS subjects, patients with RRMS were found to have increased modular connectivity and higher local clustering, highlighting increased local processing in both GM and WM. Both groups presented increased modularity and clustering coefficients in comparison to healthy controls. SVM algorithms achieved 97% accuracy using the clustering coefficient as classifier derived from GM and 65% using WM from probabilistic tractography and 67% from modularity of FA maps to differentiate between CIS and RRMS patients. We demonstrate a clear increase of modular and local connectivity in patients with early RRMS in comparison to CIS and healthy subjects. Based only on a single anatomic scan and without a priori information, we developed an automated and investigator-independent paradigm that can accurately discriminate between patients with these clinically similar disease entities, and could thus complement the current dissemination-in-time criteria for clinical diagnosis.

• Morphological alterations and microstructural changes are related to fatigue in multiple sclerosis • Thalamic alterations in particular were related to fatigue in early MS • Fatigued patients exhibited subjective but not measurable cognitive impairment • Compensatory processes help preserve or maintain cognitive performance but also contribute to fatigue.

DMF treatment response is reflected by lower circulating lymphocytes and specific lymphocyte subsets. Changes in the cellular immune profiles under DMF treatment are clinically relevant and might serve as a surrogate marker of treatment response.

White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions.