Background

Serum neurofilament light chain (sNfL) reflects neuro-axonal damage and may qualify as a biomarker of suboptimal response to disease modifying therapy (DMT).

Objectives

To investigate the predictive value of sNfL in clinically isolated syndrome (CIS) and relapsing-remitting (RR) MS patients with established DMT for future MS disease activity in the Swiss MS Cohort Study.

Methods

All patients were on DMT for at least 3 months. sNfL was measured 6 or 12-monthly with the NF-light^®assay. The association between sNfL and age was modeled using a generalized additive model for location scale and shape. Z-scores (sNfLz) were derived thereof, reflecting the deviation of a patient sNfL value from the mean value of same age healthy controls (n=8865 samples). We used univariable mixed logistic regression models to investigate the association between sNfLz and the occurrence of clinical events (relapses, EDSS worsening [≥1.5 steps if EDSS 0; ≥1.0 if 1.0-5.5 or ≥0.5 if >5.5] in the following year in all patients, and in those fulfilling NEDA-3 criteria (no relapses, EDSS worsening, contrast enhancing or new/enlarging T2 lesions in brain MRI, based on previous year). We combined sNfLz with clinical and MRI measures of MS disease activity in the previous year (EDA-3) in a multivariable mixed logistic regression model for predicting clinical events in the following year.

Results

sNfL was measured in 1062 patients with 5192 longitudinal samples (median age 39.7 yrs; EDSS 2.0; 4.1% CIS, 95.9% RRMS; median follow-up 5 yrs). sNfLz predicted clinical events in the following year (OR 1.21 [95%CI 1.11-1.36], p<0.001, n=4624). This effect increased in magnitude with increasing sNfLz (sNfLz >1: OR 1.41 [95%CI 1.15-1.73], p=0.001; >1.5: OR 1.80 [95%CI 1.43-2.28], p<0.001; >2: OR 2.33 [95%CI 1.74-3.14], p<0.001). Similar results were found for the prediction of future new/enlarging T2 lesions and brain volume loss. In the multivariable model, new/enlarging T2 lesions (OR 1.88 [95%CI 1.13-3.12], p=0.016) and sNfLz>1.5 (OR 2.18 [95%CI 1.21-3.90], p=0.009) predicted future clinical events (n=853), while previous EDSS worsening, previous relapses and current contrast enhancement did not. In NEDA-3 patients, change of sNfLz (per standard deviation) was associated with a 37% increased risk of clinical events in the subsequent year (OR 1.37 [95%CI 1.04-1.78], p=0.025, n=587).

Conclusions

Our data support the value of sNfL levels, beyond the NEDA3 concept, for treatment monitoring in MS clinical practice.

Background

Intrathecal IgM synthesis was reported to be associated with higher clinical disease activity and severity. We found an association also with earlier use of high efficacy treatments in relapsing MS (RMS).

Objectives

To explore whether patients with intrathecal IgM synthesis show a) higher serum neurofilament light chain levels (sNfL) as a reflection of neuronal damage, or b) signs of increased disease severity in cerebral MRI, in patients with RMS followed in the Swiss MS Cohort Study.

Methods

487 patients were categorized by presence of oligoclonal IgG bands (OCGB) and intrathecally produced IgG/M:

1) OCGB-/IgG-/IgM- (reference [ref]);

2) OCGB+/IgG-/IgM-;

3) OCGB+/IgG+/IgM- and

4) OCGB+/IgG+/IgM+.

sNfL was measured (at baseline and every 6- or 12 months) with the NF-light^® assay. Age-dependent sNfL z-scores (sNfLz) were modelled in 8865 healthy control samples to reflect the deviation of a patient sNfL value compared to mean values observed in same age healthy controls. Yearly T2 lesion number and occurrence of new/enlarging T2 lesions were automatically assessed in cerebral MRIs and checked manually. Contrast enhancing lesions (CEL) were manually quantified. Linear or negative binomial mixed models were used to investigate the associations between the four CSF Ig patterns and longitudinal sNfLz and MRI measures, adjusted for DMT and other covariates.

Results

IgM+ patients had higher sNfLz vs reference (estimate 0.50 [CI 0.12, 0.89], p=0.011), whereas those with only OCGB+ (0.11 [-0.28, 0.50], p=0.582) or with OCGB+/IgG+ (0.20 [-0.16, 0.56], p=0.270) did not (n=2970 observations). This was confirmed when analyzing only untreated patients adjusting for T2 and CEL numbers (1.16 [0.47, 1.86], p<0.01 vs 0.58 [-0.11, 1.27], p=0.1022 vs 0.51 [-0.11, 1.13], p=0.108 vs ref, respectively) (n=234).

IgM+ patients had 2.28-fold more T2 lesions ([1.51, 3.44], p<0.01) vs ref; for patients with only OCGB+ (1.61 [1.07, 2.43], p=0.0237) or OCGB+/IgG+ (1.58 [CI 1.08, 2.32], p=0.0179) (n=1580) this association was weaker.

IgM+ was associated with a 2.47-fold risk for new/enlarging T2 lesions on yearly follow-up MRIs vs ref (2.47 [1.28, 4.78], p<0.01) but not the two other patient groups (1.84 [CI 0.93; 3.65], p=0.0799 and 1.61 [CI 0.87; 2.95], p=0.1280) (n=861).

Conclusions

Intrathecal IgM synthesis was consistently associated with quantitative measures of neuro-axonal injury and disease severity in RMS. Our findings strongly support the clinical utiliy of this biomarker.

Background

In relapsing MS, blood NfL has emerged as a promising biomarker of disease activity and worsening. The ability of serum NfL (sNfL) to detect relapse-independent disability progression is less well established.

Objectives

We investigated whether patients followed in the Swiss Multiple Sclerosis Cohort (SMSC) without any relapses during follow-up, had higher sNfL levels when experiencing confirmed disability progression independent of relapses (PIRA) as compared to stable patients. Secondly, we explored whether baseline (BL) sNfL could predict PIRA.

Methods

BL and 6- or 12-monthly follow-up sNfL were measured by Simoa NF-light^® assay in 4608 samples from 806 relapse-free MS patients and 8865 serum samples from 4133 healthy controls (median age 45 yrs). Age-dependent sNfL z-scores (sNfLz) were modeled in healthy controls using a generalised additive model for location scale and shape to reflect the deviation of a patient sNfL value from the mean value of same age healthy controls. PIRA was defined as an EDSS increase of ≥1.5 steps if baseline EDSS 0, ≥1.0 if 1.0-5.5, or ≥0.5 if >5.5, confirmed after ≥6 months. We used mixed effects models to investigate the association between PIRA, clinical parameters, disease modifying treatment, and log(sNfL) as dependent variable at each sampling. The predictive value of BL sNfLz was investigated by uni- and multivariable Cox proportional hazards models.

Results

806 (4608 samples) of 1399 patients in the SMSC did not experience relapses during a median follow-up of 4.7 years (57.6%; BL: 715 RRMS, 43 SPMS, 48 PPMS; median age 42 yrs; samples/patient: 5; EDSS 2.0). PIRA occurred in 153/806 (19.0%). In a multivariable model, sNfL was positively associated with age (1.7%/year [95%CI 1.5;2.0], p<0.001) and EDSS at BL (7.6%/step, [5.8;9.6], p<0.001), whereas it was decreased when sampled during monoclonal antibody therapy (-10.8%, [-14.7;-6.6], p<0.001) or oral MS treatments (-10.4%, [-14.1;-6.5%], p<0.001) as compared to untreated timepoints. Importantly, patients experiencing PIRA had 11.6% higher sNfL levels, compared with stable patients (4.5;19.2, p=0.001). The hazard of future PIRA increased by 23.5% (8.3;40.8, p=0.002) per 1 standard deviation higher BL sNfLz. This finding was confirmed after adjusting for age, EDSS score and treatment at BL (27.8%, [11.5;46.5], p<0.001; sNfLz > 2: 2.5-fold risk [95%CI 1.7-3.9], p<0.001 for PIRA event vs. sNfLz < 2).

Conclusions

Our data support the value of sNfL to capture and predict neuro-axonal injury leading to disability progression independent from relapses.

Background

Serum neurofilament light chain (sNfL) levels reflect neuroaxonal damage and relate to disease activity in MS. sNfL may qualify as well as a biomarker of suboptimal treatment response to disease modifying therapies (DMT). Establishment of age-dependent reference ranges in healthy controls is a prerequisite for developing this biomarker for clinical use.

Objectives

To compare on-treatment sNfL levels with values from a healthy control cohort and to investigate the effect of DMTs on sNfL levels in patients from the Swiss MS Cohort Study.

Methods

sNfL was measured (at baseline and every 6- or 12 months) with the NF-light® assay. Age-dependent sNfL z-scores (sNfLz) were modeled in healthy controls using a generalized additive model for location scale and shape to reflect the deviation of a patient sNfL value from the mean value of same age healthy controls. Linear mixed models were used to investigate the associations between clinical characteristics, DMT and longitudinal sNfLz. Interaction terms and splines were used to model sNfLz and for comparison log(NfL), and their dynamics under treatment.

Results

sNfL was measured in 1368 patients with 7550 longitudinal samples (baseline: median age: 41.9 yrs; 5.4% CIS, 83.2% RRMS, 5.6% SPMS, 5.8% PPMS; median EDSS: 2.0; median follow-up: 4.6 yrs) and 4133 healthy controls with 8865 samples (median age: 44.8 yrs). In the multivariable model, sNfLz increased with EDSS (0.131/step, [95% CI 0.101;0.161]), recent (<120 days) relapse (0.739 [0.643;0.835]) decreased with age (-0.014/year [-0.02;-0.009]), and time on DMT (-0.040/year [-0.054;-0.027]); sNfLz were lower when sampled while on more effective DMT (oral versus platform injectables: -0.229 [-0.344;-0.144]; monoclonal antibodies (mAB) versus platform injectables: -0.349 [-0.475;-0.224]), (p<0.001 for all associations). sNfLz were inversely associated with the hierarchy in efficacy of mAB over orals and orals over platform therapies with regard to slope and extent of decrease (interaction between time under DMT and DMT class: p<0.001). sNfLz, but not log(NfL) showed normalization of sNfL levels by mAB to healthy control levels.

Conclusions

The dynamic change of sNfLz on DMT reflects closely their relative clinical efficacy and is more meaningful than log(sNfL) by excluding age as a confounding factor. Use of sNfLz based on a large normative database as an age-independent sNfL measure improves the accuracy of the sNfL signal and hence their clinical utility.

Background

Graph theory is used to study brain connectivity, i.e. connectomes, estimated with diffusion magnetic resonance imaging (dMRI). Previous studies have already investigated the correlation between some network measures and the Expansion Disability Status Scale (EDSS), which assesses the clinical worsening of multiple sclerosis (MS) patients.

Objectives

We investigated connectivity changes between healthy controls (HC) and relapsing remitting (RR) patients and tested whether such differences correlate with EDSS, comparing the effectiveness of various definitions of “connection strength” using different microstructural models.

Methods

dMRI was acquired for 67 HC (39F, 37±7yrs) and 49 RR (33F, 37±4yrs). Connectomes were created with deterministic tractography and weighting the connections by 1) number of streamlines (NOS) between grey-matter regions and, 2) mean value of quantitative scalar maps, estimated using state-of-the-art microstructural models, along the streamlines, notably: fractional anisotropy, FA; axial AD, radial RD and mean diffusivity MD; Intra Neurite and Isotropic Volume Fractions, ICVF and ISOVF; orientation dispersion, OD; Neurite volume fraction, INTRA; Extra-neurite transverse and mean diffusivity EXTRATRANS and EXTRAMD. We computed 5 network measures from each connectome: Density (ratio between actual and possible connections); Efficiency (capability of transferring and processing information); Modularity (network segregation); Clustering Coefficient (degree to which nodes tend to cluster together); Mean Strength (average of the sum of the edge weights connected to a node).

Results

The network measures that significantly differ between the 2 groups were: Efficiency for ICVF p=0.031, AD p<0.01, RD p<0.01, EXTRATRANS p=0.019 and MD p<0.01 connectomes; Clustering Coefficient for AD p=0.015, RD p=0.013, EXTRATRANS p=0.021 and MD p<0.01 connectomes; Mean Strength for ICVF p=0.019, INTRA p=0.037, AD p=0.011, RD p<0.01, EXTRATRANS p=0.014 and MD p<0.01 connectomes. Only Modularity significantly correlate with EDSS for NOS p=0.047, FA p=0.049, ICVF p=0.041 and INTRA p=0.030 connectomes. All tests accounted for age, sex and density as confounding factor.

Conclusions

The maps discriminating more HC from MS patients were AD, RD, MD and EXTRATRANS. The microstructure features along the tracts with the highest correlation to EDSS were those investigating axonal integrity (FA, ICVF and INTRA). Modularity was the metric most correlated with EDSS.

Background

The pathogenesis of neurodegeneration in multiple sclerosis (MS) is multifactorial and the determinants of brain atrophy rates are not completely understood.

Objectives

To investigate the association between annualized atrophy rate (AAR) of multiple brain measures (regional cortical thickness (CTh), volumes of basal ganglia, thalamus, white matter, gray matter, brain and brain parenchymal fraction (BPF)) and: (1) annualized rate of new and enlarging white matter lesions (WMLs); (2) annualized rate of resolved WMLs; (3) occurrence of progression independent of relapse activity (PIRA) during follow-up.

Methods

We included 1573 1.5T or 3T brain MRI scans from 378 patients of the Swiss MS Cohort Study (331 relapsing-remitting MS (RRMS), 27 clinically isolated syndrome (CIS), 11 secondary-progressive MS (SPMS), 9 primary-progressive MS (PPMS); 70% female; median age: 41.9 yrs; disease duration: 8.3 yrs; EDSS: 2.0; follow-up time: 4.0 yrs). Longitudinal changes in WMLs were obtained using an automated prototype (LeMan-PV). Brain volumes and CTh AARs were obtained using FreeSurfer longitudinal pipeline (v6.0) after WMLs filling. In patients fulfilling PIRA an EDSS progression had to be confirmed ≥6 months after the index event. Multivariable generalized linear models were used to model the association between AAR (dependent variable) and independent variables (1-3), correcting for age, sex, disease duration and baseline EDSS. p-values were adjusted for Bonferroni multiple comparison correction; for vertex-wise CTh analysis, Monte Carlo Z simulation was performed (cluster threshold p<0.05).

Results

We found positive associations between annualized rate of new and enlarging WMLs and (i) CTh AAR of 8 extensive clusters (bilateral frontal, temporal and occipital regions and right insula, all p<0.01) and (ii) AAR of: caudate bilaterally (p=0.02), white matter volume, brain volume and BPF (p<0.001 for all).

We also found a negative association between annualized rate of resolved WMLs and CTh AAR in 3 cortical clusters (right insula, precentral area and anterior cingulate region, all p<0.05); no associations with AAR of volumes emerged.

57 patients fulfilled PIRA whereas 295 experienced no EDSS progression events: no significant differences in AAR measures were found between these two groups.

Conclusions

In a large cohort of MS patients, with a median follow-up of 4 years, local radiological inflammatory and reparative activity were associated with AAR in multiple brain regions. PIRA did not seem to be related to increased AAR in any of the regions studied.

Background

Neurofilament light polypeptide (NfL) is a neurofilament protein highly expressed in myelinated axons. Increased serum NfL (sNfL) concentration indicates the presence of axonal damage in patients with multiple sclerosis (MS). Until now, the potential effects of this axonal damage on brain connectivity have never been investigated.

Objectives

We studied the relationship between active inflammation measured by sNFL and structural connectivity alterations detectable by global network metrics estimated with diffusion MRI.

Methods

Diffusion MRI, T1-weighted and FLAIR sequences were acquired on 74 patients (44F, 44.9±14.6yrs, 50 relapsing-remitting and 24 progressive) and sNfL levels were measured from blood samples in the same session. Volume of white-matter lesions was computed on FLAIR with an automatic in-house tool. To build the connectomes we 1) performed deterministic tractography on diffusion MRI, 2) segmented the grey matter in 85 regions using T1 images, and 3) quantified the connection strength of each pair of regions by counting the streamlines between them. From each connectome we extracted 5 global metrics: Density (ratio between actual and possible connections), Efficiency (capability of transferring and processing information); Modularity (network segregation); Clustering Coefficient (degree to which nodes tend to cluster together); Mean Strength (average of the sum of the edge weights connected to a node). Since discrepancies in density may affect other metrics, we first tested its correlation with sNFL, then we performed partial correlations of the last 4 metrics with sNFL using age, sex and density as covariates.

Results

We found negative correlation between density and sNfL (R=-0.252 p=0.05) indicating that high axonal damage is associated with reduced number of connections. Efficiency and mean strength showed a strong anti-correlation with sNfL (R=-0.325 p=0.011 and R=-0.475 p<0.001), while modularity and clustering coefficient seemed not related to axonal damage (R=0.183 p=0.162 and R=-0.215 p=0.099). Finally, a positive association with sNfL was found for both the lesions volume and the Expansion Disability Status Scale (p=0.011 R=0.323 and p=0.038 R=0.267), confirming previous results.

Conclusions

We showed that high values of sNfL are associated with global connectivity damage (reduced number of connections, efficiency and mean strength) confirming the utility of network-based connectivity metrics to assess MS disease impact.

Background

Postmortem MRI provides precious insights into the relation of MRI metrics to pathoanatomical features of multiple sclerosis (MS) and can help to understand the basis of damage and repair.

Objectives

To investigate the respective features of MS lesions in the cortex and in the white matter using multiparametric postmortem MR imaging at 3T and identify discriminant characteristics of white matter lesion subgroups.

Methods

We scanned three fixed brains of secondary-progressive MS patients (mean disease duration 15.3 years) on a standard clinical 3T-MRI scanner with following sequences: Magnetization Transfer Saturation (MTsat), T1-relaxometry (T1-rt), Myelin Water Fraction (MWF) and Diffusion Tensor - Fractional Anisotropy (DTI-FA). We compared these metrics between (i) cortical lesions (CL, n=118) and normal-appearing grey matter (NAGM, n=186) and (ii) white matter lesions (WML, n=140) and normal-appearing white matter (NAWM, n=53) using a Mann-Whitney U test. Then, we analyzed the differences between different subgroups of WML (periventricular lesions -PVL-, n=38, WM part of leukocortical lesions -WMLCL-, n=36, subcortical lesions -SCL-, n=66, and areas of “dirty white matter” -DWM-, n=15) by performing a Kruskal-Wallis test and a Mann-Whitney U tests for direct comparison. Bonferroni correction for multiple-testing was applied.

Results

CL exhibited lower MTsat (p<0.001), higher T1-rt (p<0.001) and MWF (p<0.01) than normal appearing cortical tissue. WML showed lower MTsat (p<0.001), higher T1-rt (p<0.001), and lower MWF (p<0.001) than normal appearing white matter. DTI-FA did not differ between CL/WML and NAWM/NAGM. MTsat values were lower in the PVL (p<0.001) and higher in the DWM (p<0.001) in comparison to all other lesion subgroups. T1-rt were higher in PVL (p<0.001) compared to the other lesion subgroups. MWF values were higher in DWM and SCL (p<0.01), not statistically different between PVL and WMLCL. DTI-FA values were lower in WMLCL in comparison to all other subgroups (p<0.01) and did not differ between the other categories.

Conclusions

Postmortem MRI metrics in WML/CL as well as in different subgroups of WML, are compatible with myelin damage and tissue destruction. Interestingly, MWF was higher in CL than in NAGM, which might correspond to a predominance of “myelin blistering” pathology in the cortex. Ongoing work aims to directly correlate our findings with detailed histopathological characterization including electron microscopy of myelin damage.