Background

Glial fibrillary acidic protein (GFAP) is released into the cerebrospinal fluid and blood upon astroglial injury and activation, one of the hallmarks of progressive multiple sclerosis (PMS). It is unclear whether blood GFAP levels are associated with disability accumulation in secondary progressive MS (SPMS).

Objectives

To explore GFAP as a prognostic biomarker of disability worsening in patients with active and/or non-active SPMS (aSPMS and/or naSPMS) in the Phase 3 EXPAND study.

Methods

In this post-hoc analysis from the EXPAND study, baseline (BL) GFAP was quantified in EDTA plasma samples using Single Molecule Array technology. GFAP was categorized as high/low based on the gender stratified 80 percentile. The effect of GFAP on time to Expanded Disability Status Scale [EDSS] 7 (wheelchair restricted) was assessed using a Cox regression model adjusted for age, gender, disease duration, treatment, relapses in the 24 months prior to study start, and BL EDSS. Subgroup analyses were conducted in patients with aSPMS/naSPMS (with/without relapses ≤24 months prior to study entry, and/or gadolinium-enhancing T1 lesions at BL) and were also stratified by gender.

Results

Samples were available for 1405 of the 1651 patients randomized in the EXPAND study; median GFAP levels (pg/mL) were 119.6 (male) and 141.4 (female). Overall, the risk of reaching EDSS 7 was higher in patients with high BL GFAP (96%: high vs low GFAP, [34/281, 12.1%] vs [54/1117, 4.8%]; HR 1.96 [1.27; 3.03]; p=0.0024). Interestingly, the increased risk of reaching EDSS 7 was mainly seen in females (23/169; 13.6%] vs [34/673; 5.1%]; HR 2.22 [1.30; 3.80]; p=0.0035), and not significant in males ([11/112, 9.8%] vs [20/444, 4.5%]; HR 1.45 [0.67; 3.12]; p=0.3457). Increase in risk of reaching EDSS 7 was mainly observed in naSPMS patients (high GFAP [14/133; 10.5%] vs low GFAP [22/570; 3.9%]; HR 3.40 [1.71; 6.75]; p=0.0005) and was not significant in aSPMS patients (high GFAP [20/144; 13.9%] vs low GFAP [30/521; 5.8%]; HR 1.58 [0.88; 2.82]; p=0.1250). However, associations between BL GFAP levels and time to 6-months confirmed disability progression showed similar trends, but were less pronounced.

Conclusions

Blood GFAP appears to be a prognostic biomarker of disability worsening. The relevance of the gender difference and the stronger correlations found in SPMS patients with non-active versus active disease needs further investigation.

Background

Background
Neuromyelitis optica spectrum disorders (NMOSD), anti-MOG-antibody associated disease (MOGAD) and multiple sclerosis (MS) may be difficult to differentiate. Detection of antibodies (Ab) targeting AQP4 and MOG is the diagnostic gold standard for the former two diseases, but has limited sensitivity and long laboratory turnaround time. Neutrophil granulocyte (NG) invasion of brain tissue is a key differentiator of NMOSD from MS, and has also been described in MOGAD.

Objectives

Objectives
To examine the capability to differentiate NMOSD/MOGAD from MS by the profile of secreted primary (elastase (Ela); myeloperoxidase (MPO)) and secondary (matrix metalloproteinase-8 (MMP-8); neutrophil gelatinase-associated lipocalin (NGAL)) neutrophil granule products in CSF.

Methods

Methods
CSF from patients with NMOSD (n=42), MOGAD (n=6) and RRMS (n=41) were evaluated for Ela, MPO, MMP-8, NGAL, and compared with markers of neuronal (NfL) and astrocyte (GFAP, S100B) damage by conventional ELISA or single molecule array assay. CSFs from healthy controls (HC) (n=25) served as reference. The association between biomarkers and disease groups was assessed in linear models. The kinetic change of biomarkers in function of time since last relapse was modelled across disease groups. ROC curves and area under the curve (AUC) were calculated to estimate the potential to differentiate NMOSD/MOGAD from RRMS in acute disease phase (≤20 days after relapse), as well as between acute NMOSD and MOGAD. The association of biomarkers with EDSS in acute NMOSD and RRMS was assessed by linear models and Spearman correlation.

Results

Results
All disease groups had elevated NfL vs HC (p<0.01), while GFAP levels were increased only in NMOSD (p<0.01). In acute NMOSD, all 4 NG markers were increased vs HC and acute RRMS (all p<0.01). In MOGAD, Ela, MPO and MMP-8 were increased vs HC (p<0.025) and acute RRMS (p<0.04). AUC in ROC analyses comparing acute NMOSD/MOGAD vs acute RRMS was high (Ela and NGAL: 0.91; MPO: 0.82; MMP-8: 0.81). In acute NMOSD, S100B and GFAP levels were increased in 89% (AUC=0.82) and 83% (AUC=0.80) of patients, respectively, vs median values of MOGAD. In acute NMOSD, EDSS scores correlated with all 4 NG markers (all p<0.01), and GFAP (p<0.031), but not with NfL and S100B (both p=0.21).

Conclusions

Conclusion
NG-specific biomarkers correlate with current EDSS scores in NMOSD. They show high sensitivity and specificity for rapid differentiation of acute NMOSD and MOGAD vs RRMS, similar to those reported for Ab against AQP4 and MOG. As the 4 NG biomarkers can be measured within few hours, as compared to an up to 2-week turnaround time for gold-standard cell-based assays for AQP4 and MOG, they could support individual decision making for acute therapeutic intervention. Further, increased S100B and GFAP levels differentiate acute NMOSD from MOGAD. NG markers may have a role in the diagnosis of Ab-negative NMOSD.

Background

Pregnancy in MS typically goes along with reduced disease activity in the third trimester, followed by an increase in relapse frequency postpartum. Neurofilament light chain levels in serum (NfL) is a specific biomarker of neuroaxonal injury. Increased NfL levels are associated with relapses and MRI activity, while disease modifying treatment (DMT) response is reflected by a decrease of NfL.

Objectives

The objective of this study was to evaluate whether interrupting DMT due to pregnancy leads to increased NfL levels in MS.

Methods

We investigated prospectively documented pregnancies in the Swiss MS Cohort Study. Serum samples were collected 6- or 12-monthly and were analyzed by Simoa NF-light® assay. Uni- and multivariable mixed effect models were used to investigate associations between clinical characteristics and longitudinal NfL levels.

Results

We investigated 72 pregnancies in 63 relapsing MS patients (median age 31.4; disease duration 7.1 years; EDSS 1.5 at last visit before birth). In total, 433 samples were included: 92 during pregnancy or up to initiation of DMT but max. 9 months postpartum (pregnancy/post-partum period, pp), 167 prior to pp and 174 after the pp. Four patients had no DMT before, during and after pregnancy. DMT was continued in 13/72 pregnancies (>6 months during pregnancy: 6 rituximab/ocrelizumab, 4 natalizumab, 1 interferon-beta 1a i.m., 1 fingolimod and 1 glatiramer acetate). In univariable analysis, NfL levels were on average 22% higher during vs. outside the pp (β: 1.22, 95%CI: 1.10-1.35; p<0.001). We observed 29 relapses during the pp. In a multivariable analysis, relapses (within 120 days before serum sampling) were associated with 98% higher NfL (β: 1.98, 95%CI: 1.75-2.25; p<0.001); NfL was 7% higher per EDSS step increase (β: 1.07, 95%CI: 1.01-1.12; p=0.013) and on average 13% higher during vs. outside the pp (β: 1.13, 95%CI: 1.03-1.24; p=0.009). The effect of the pp on NfL disappeared after including DMT exposure (yes/no) at the sampling timepoint to the model (β:1.07, 95%CI: 0.97-1.18; p=0.178). Patients sampled during DMT had on average 12% lower NfL levels compared to patients without (β:0.88, 95%CI: 0.79-0.98; p=0.019).

Conclusions

Higher NfL levels were found during pp. This increase was independent of relapses suggesting increased subclinical disease activity during this time span. After including DMT into the model the effect of pregnancy on NfL disappeared: strategies allowing to continue DMT during pregnancy may be warranted.

Background

Neuromyelitis optica spectrum disorders (NMOSD) are autoimmune mediated astrocytopathies. Glial fibrillary acidic protein (GFAP) and S100B, two astrocyte specific, and neurofilament light chain (NfL), a neuron specific biomarker are reported to be elevated in CSF and serum or plasma in acute phases of NMOSD. Serum NfL is a predictor of relapse activity in multiple sclerosis (MS). However, whether serum levels of NfL (sNfL), GFAP (sGFAP) or S100B (sS100B) levels can be prognostic biomarkers for future acute disease activity in NMOSD has not been elucidated.

Objectives

To test the prognostic potential of sGFAP, sS100B and sNfL levels during remission phase as biomarker for future relapses in NMOSD with aquaporin-4-IgG.

Methods

Median values of sGFAP, sS100B and sNfL were calculated from 47 serum samples from 18 patients in remission (>180 days after last relapse), followed for up to 10 years, and marked cut-off levels for “high” and “low” sGFAP (141.6 pg/mL), sS100B (8.6 pg/mL), and sNfL (33.9 pg/mL), respectively. Kaplan-Meier analysis, univariable and a multivariable (adjusted for age, sex, time from recent relapse and treatment) Cox-hazard model were used to compare the time to and hazard risk of the next relapse between the high and low groups for all three markers.

Results

Twenty-five first post-relapse/remission phase samples from these 18 patients (11 had one relapse, 7 had two relapses) were selected for analyses. Patients in the high sGFAP group experienced future relapses earlier than those with low sGFAP levels (median 3710 versus 922 days, p = 0.0047) and had higher risk of future relapses (unadjusted hazard ratio (HR): 5.6 [95% CI 1.5–21.0], p = 0.010; adjusted hazard ratio: 9.5 [95% CI 1.9–47.0], p = 0.0061). In contrast, high sS100B and sNfL levels were unable to identify patients at increased risk for relapses.

Conclusions

We illustrate the prognostic capacity of an astrocyte specific marker, sGFAP, for future relapses in stable NMOSD. This further supports the value of this blood biomarker for potential future clinical application in guiding and monitoring treatment response of patients with NMOSD. The failure of sNfL as a neuronal marker in this capacity for NMOSD may reflect the pathogenetic differences between this disease and MS. The failure of sS100B may result from its pharmacokinetic profile as a short-lived marker in acute NMOSD, but not in stable disease.

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

Quantitative susceptibility mapping (QSM) identifies iron accumulation and myelin loss in smoldering white matter lesions (WMLs). Yet, QSM may be also used to provide a broader understanding of focal and diffuse MS pathology.

Objectives

To study QSM features across WMLs, to assess myelin and axonal loss in WMLs with different QSM features and to quantify QSM pathology in normal-appearing white and cortical grey matter (NAWM, NAGM).

Methods

Ninety-one MS patients (62 RRMS, 29 PMS) and 72 healthy controls (HC) underwent QSM, myelin water imaging (MWI) and multishell diffusion at 3T MRI. In WMLs, cortical lesions (CLs), NAWM and NAGM, we extracted mean QSM, myelin water fraction (MWF) and neurite density index (NDI). WMLs were classified into 5 groups according to their appearance on 3D-EPI QSM: (i) isointense; (ii) with hyperintense rim, Rim+ (iii); with hypointense rim relative to the lesion core, hypo Rim; (iv) hyperintense; (v) hypointense. Mann-Whitney and Kruskal-Wallis test with Dunn’s correction for multiple comparison were used to compare (a) lesion types and (b) specific lesions vs all other WMLs. Voxel-wise comparisons of NAWM QSM were performed using Threshold-Free Cluster Enhancement (TFCE) clustering. Cortical analysis of QSM NAGM and GM-HC was performed using FreeSurfer and compared using a General Linear model (GLM).

Results

Of 1136 WMLs in QSM maps, we detected: (i) 314 (27.6%), (ii) 183 (16.1%), (iii) 16 (1.41%), (iv) 577 (50.8%) and (v) 46 (4.05%) WML. All WML exhibited lower NDI than NAWM and WM-HC (P<0.0001). Isointense lesions exhibited higher NDI (P=0.0115) and MWF (P<0.0001) than other WMLs. Rim + and hyperintense lesions exhibited lower MWF than NAWM and WM-HC (P<0.0001). Rim + lesions showed lower MWF and NDI than other WML types (P<0.001). Hypo Rim+ lesions and hypointense lesions exhibited higher MWF than other WMLs (P=0.0006, P<0.05). Hyperintense lesions exhibited lower MWF than other WMLs types (P<0.01) except Rim+ lesions. TFCE and vertex-wise cortical surface analysis showed areas throughout the NA tissue, where QSM is either lower or higher compared to healthy tissue in HC and in PMS compared to RMS (P<0.01).

Conclusions

QSM is sensitive to diffuse and focal pathology with various myelin and axonal characteristics. We hypothesize that isointense WMLs show high repair activity, hypointense WMLs are remyelinated lesions and hyperintense WMLs are chronic inactive lesions. MRI-histopathology work is ongoing to confirm these findings.

Background

Glial fibrillary acidic protein (GFAP) is released into the cerebrospinal fluid and blood upon astroglial injury and activation, one of the hallmarks of progressive multiple sclerosis (PMS). It is unclear whether blood GFAP levels are associated with disability accumulation in secondary progressive MS (SPMS).

Objectives

To explore GFAP as a prognostic biomarker of disability worsening in patients with active and/or non-active SPMS (aSPMS and/or naSPMS) in the Phase 3 EXPAND study.

Methods

In this post-hoc analysis from the EXPAND study, baseline (BL) GFAP was quantified in EDTA plasma samples using Single Molecule Array technology. GFAP was categorized as high/low based on the gender stratified 80 percentile. The effect of GFAP on time to Expanded Disability Status Scale [EDSS] 7 (wheelchair restricted) was assessed using a Cox regression model adjusted for age, gender, disease duration, treatment, relapses in the 24 months prior to study start, and BL EDSS. Subgroup analyses were conducted in patients with aSPMS/naSPMS (with/without relapses ≤24 months prior to study entry, and/or gadolinium-enhancing T1 lesions at BL) and were also stratified by gender.

Results

Samples were available for 1405 of the 1651 patients randomized in the EXPAND study; median GFAP levels (pg/mL) were 119.6 (male) and 141.4 (female). Overall, the risk of reaching EDSS 7 was higher in patients with high BL GFAP (96%: high vs low GFAP, [34/281, 12.1%] vs [54/1117, 4.8%]; HR 1.96 [1.27; 3.03]; p=0.0024). Interestingly, the increased risk of reaching EDSS 7 was mainly seen in females (23/169; 13.6%] vs [34/673; 5.1%]; HR 2.22 [1.30; 3.80]; p=0.0035), and not significant in males ([11/112, 9.8%] vs [20/444, 4.5%]; HR 1.45 [0.67; 3.12]; p=0.3457). Increase in risk of reaching EDSS 7 was mainly observed in naSPMS patients (high GFAP [14/133; 10.5%] vs low GFAP [22/570; 3.9%]; HR 3.40 [1.71; 6.75]; p=0.0005) and was not significant in aSPMS patients (high GFAP [20/144; 13.9%] vs low GFAP [30/521; 5.8%]; HR 1.58 [0.88; 2.82]; p=0.1250). However, associations between BL GFAP levels and time to 6-months confirmed disability progression showed similar trends, but were less pronounced.

Conclusions

Blood GFAP appears to be a prognostic biomarker of disability worsening. The relevance of the gender difference and the stronger correlations found in SPMS patients with non-active versus active disease needs further investigation.

Background

The concept of no evidence of disease activity-3 (absence of brain MRI and clinical disease activity; NEDA-3) in multiple sclerosis (MS) reflects disease activity with limited sensitivity. The added value of neurofilament light chain levels in serum (sNfL) to NEDA-3 has not yet been investigated.

Objectives

To assess whether sNfL allows to identify among patients with and without NEDA-3 status those at higher risk of future disease activity and accelerated brain volume loss.

Methods

We analyzed 369 samples from 155 early relapsing-remitting MS patients (SET study). sNfL levels and brain MRI scans were evaluated annually. The comparison of subgroups defined by high or low sNfL (>90^th or <90^th percentile of healthy controls of the same age) and NEDA-3 status was performed by generalized estimating equation models. Changes in global and regional brain volumes were calculated on three-dimensional T1-weighted scans.

Results

Patients with disease activity (EDA-3) in the preceding year and high sNfL, compared to those with low sNfL, had: a) higher odds of EDA-3 in the following year (87% versus 58%; OR 4.39, 95%-CI:2.18, 8.94; p<0.001), b) greater whole brain volume loss during the following year (0.39%, 95%-CI:-0.63, -0.16; p<0.001) and c) greater whole brain volume loss (0.61%, 95%-CI:-0.66, -0.17; p<0.001) during the preceding year. Accordingly, NEDA-3 patients with high sNfL showed a trend for a return of disease activity (EDA-3) in the following year compared with those with low sNfL (57% versus 31%).

Conclusions

High sNfL levels are associated with increased future risk of disease activity and accelerated brain volume loss. Adding of sNfL improves the prognostic value of the NEDA-3 concept.

Background

Microstructural biophysical models reconstructed from advanced diffusion MRI (dMRI) data provide quantitative measures (qMs), which inform about the brain tissue microenvironment, based on different assumptions.

Objectives

To compare the sensitivity of available qMs to focal pathology in multiple sclerosis (MS), and to explore which qMs– or combinations of qMs – are best correlated with patients’ disability.

Methods

dMRI (1.8 mm isotropic resolution, 149 directions, b-values were 0, 700, 1000, 2000, 3000 s/mm²) was acquired from 67 relapsing-remitting and 33 progressive MS patients (median EDSS: 2.5). The qMs for the isotropic and intra-axonal compartments were derived from the following available models: Ball and Stick, NODDI, SMT-NODDI, MCMDI, NODDIDA, DIAMOND, Microstructure Bayesian approach (MB) and microstructure fingerprinting. In total, 13 qMs were included and subject-wise normalized within brain tissue (nqMs).

To identify the nqMs sensitive to focal pathology, an attention-based convolutional neural network (aCNN) was built to (a) classify randomly sampled WM lesion and perilesional WM patches and (b) generate attention weights (AWs) representing the relative importance of the qMs in the classification. Twenty patients were randomly selected in the test dataset (709 lesion patches and 746 perilesional WM patches), and the rest were in the cross-validation (CV) dataset (2925 lesion patches and 3176 perilesional WM patches). The performance metric was the area under the receiver operating characteristic curve (AUC). Because of the correlation between the nqMs, which may influence the relative AWs, we performed 10-fold CV and selected the nqMS that most contributed to the classification.

To assess which nqMS – or combination of nqMS was best correlated with EDSS, we used Spearman’s correlation coefficient (ρ) with two-sided 20000 permutation tests and followed by Bonferroni correction.

Results

The test AUC was 0.911 indicating the aCNN learned the right AWs to differentiate lesions and perilesional WM. The most discriminating nqMs included isotropic and intra-axonal compartments from MB, the neural density index (NDI) from the NODDI and the intra-axonal compartment from MCMDI.

The sum of isotropic and intra-axonal compartments of the MB (sMB) showed the strongest correlation with EDSS (ρ=-0.40,corr. p<0.0001) followed by the sum of sMB and NDI (ρ=-0.30,corr. p<0.05), and the sum of sMB and intra-axonal compartment from MCMDI (ρ=-0.32,corr. p<0.05). None of the selected nqMs as a single measure and their other combinations correlated with EDSS.

Conclusions

By performing aCNN-aided selection of the openly available WM quantitative measures, we have identified the measures most sensitive to MS focal pathology; furthermore, we have derived a new contrast that – by combining the measures of isotropic and intracellular diffusion – strongly correlated with patients’ disability.

Background

Serum Neurofilament light chain (sNfL) is a biomarker of neuronal damage, reflecting disease activity, drug response, and is predictive of future disability in established multiple sclerosis (MS).

Objectives

Post hoc analysis to assess whether baseline (Month [M] 0) sNfL concentration can predict conversion to McDonald (McD) 2005 MS in patients (pts) with a first clinical demyelinating event (FCDE) receiving subcutaneous interferon β-1a (scIFNβ-1a) once (qw) or three (tiw) times weekly, or placebo (PBO) in the phase 3 trial REFLEX.

Methods

Pts randomized to scIFNβ-1a tiw (n=171) or qw (n=175), or PBO (n=171) were followed-up over 2 yrs; converters to 'clinically definite MS' switched to open label scIFNβ-1a tiw. High and low M0 sNfL subgroups were defined by median sNfL concentration (26.1 pg/ml at M0). Median (95% confidence intervals [CI]) time to McD MS (days) by treatment group and M0 sNfL subgroup was calculated by Kaplan Meier. Hazard ratios (HR; 95% CI) to determine factors influencing risk of conversion to McD MS were calculated using a univariate Cox’s proportional hazard model. A stepwise multivariate Cox’s proportional hazard model was performed using factors selected from the univariate model (threshold P<0.15). For both models, variable selection was based on a two-sided Wald test.

Results

High sNfL levels at baseline correlated with the likelihood for conversion to McD MS (low vs high M0 sNfL, HR [95% CI]: 0.58 [0.47; 0.72], P<0.001). Other baseline factors that reduced the risk of conversion to McD MS (univariate model) included: classification of FCDE (mono- vs multifocal: 0.68 [0.55; 0.83], P<0.001) and low numbers of MRI lesions (number of T2 lesions: 1.02 [1.02; 1.03], P<0.001; number of T1 gadolinium-enhancing [Gd+] lesions: 1.14 [1.11; 1.17], P<0.001; number of T1 hypointense lesions: 1.04 [1.02; 1.05]; P<0.001). Furthermore, treatment with scIFNβ-1a tiw (vs PBO: 0.53 [0.41; 0.69], P<0.001) or qw (0.71 [0.56; 0.91], P=0.006) reduced the risk of conversion to McD MS. These findings were confirmed by multivariate models for baseline sNfL subgroup (P=0.024), classification of FCDE (P<0.001), most baseline imaging findings (number of T2 lesions, number of T1 Gd+ lesions; (P≤0.001), and on-study treatment (both P<0.001).

Conclusions

Among other factors, baseline sNfL concentration was identified as a predictor of conversion to McD MS in patients with a FCDE.

Background

In the ASCLEPIOS I/II trials, ofatumumab significantly lowered serum neurofilament light (sNfL) levels, a marker of disease activity and treatment response, in the first assessment at month 3 and at all subsequent visits versus teriflunomide.

Objectives

To investigate the prognostic value of baseline sNfL for on-study disease activity and worsening in patients with relapsing MS, particularly in newly diagnosed, treatment-naïve patients.

Methods

Patients (pooled N=1882) were randomized to ofatumumab or teriflunomide, receiving treatment for up to 30 months. Patients were stratified by median baseline sNfL levels. We assessed annual on-study T2 lesion formation and brain volume loss (BVL, Jacobian integration) by sNfL category in all patients and in the subgroup of newly diagnosed within 3 year of screening without prior disease-modifying treatment (representing natural course of sNfL and disease at baseline) at month 24 or end of study. The annualized rate of new or enlarging T2 (neT2) lesions in year-2 versus year-1 was assessed in all patients by sNfL category (negative binomial model with time [in year] as offset).

Results

Patients with high sNfL (>median) levels at baseline developed more neT2 lesions per year on study than patients with low (≤median) sNfL levels (adjusted mean rate: ofatumumab: 0.95 vs 0.39, relative increase 143%, p<0.001; teriflunomide 5.28 vs 3.02, relative increase 74.5%, p<0.001). The prognostic value of baseline sNfL persists for year-2 (high vs low, ofatumumab: 0.09 vs 0.06, 64.5%, p=0.124; teriflunomide 4.53 vs 3.12, 45.6%, p=0.003. A single sNfL assessment at baseline had no prognostic value for on-study relapses and disability worsening. Patients with high baseline sNfL had higher annualized rate of BVL than patients with low sNfL (ofatumumab: 0.32% vs 0.23%, relative difference 37.3%, p=0.045; teriflunomide: 0.43% vs 0.29%, relative difference 49.4%, p<0.001). The results were consistent in the subgroup of newly diagnosed, treatment-naïve patients. The relative treatment effect of ofatumumab versus teriflunomide was similar across all measures in both the high and low sNfL groups.

Conclusions

Baseline sNfL levels were prognostic for on-study lesion formation and BVL for at least 2 years, in all patients and in the subgroup of newly diagnosed, treatment-naïve patients. sNfL levels can supplement clinical assessments and help identify patients at high risk for future disease activity.

Background

Quantification of the activity and progression of multiple sclerosis (MS) is an important tool for research on MS as well as its clinical treatment. Currently, disease activity and progression assessments rely on qualitative clinical evaluations or the acquisition of radiographic data such as magnetic resonance imaging (MRI).

Objectives

Quantifying MS disease activity (DA) and progression (DP) instead through the use of blood biomarkers would provide a significant reduction in barriers to such testing (e.g. monetary cost, time and specialized personnel requirements, invasiveness, operational difficulty, etc.). The use of an ensemble of proteins representing various biological pathways involved in MS pathophysiology would also provide useful insights into this complex and heterogeneous disease.

Methods

We investigated proteomic biomarkers associated with different levels of MS DA and DP using 205 blood serum samples from 88 patients (University Hospital Basel), extracting protein levels using Proximity Extension Assays (PEA) from Olink^TM. We then conducted a focused statistical analysis on 21 proteins that were selected for a custom MS assay panel development project based on their association with endpoints in previous studies. We corrected these protein levels using clinical data, including: age, sex, disease duration, age of the bio-banked sample, and medication status. We then compared protein levels to five different radiographic and clinical endpoints.

– Primary Endpoint: Gadolinium (Gd) enhanced lesion count

– Secondary Endpoints: T2 lesion volume, Expanded Disability Status Scale (EDSS) score, Clinically Defined Relapse Status, and Annualized Relapse Rate (ARR)

Results

In this report, we examine the univariate performance of selected proteins on the prediction of all five endpoints, comparing it to that of several multivariate machine learning techniques. We draw distinctions between the highest performing models for each endpoint and draw connections to the underlying biology governing MS activity and progression.

Conclusions

We found significant improvements in predictive power from the use of multivariate models in comparison to even the highest performing univariate techniques. The samples analyzed in this study will be re-assayed for validation purposes alongside additional cohorts in the forthcoming 21-plex custom MS proteomic assay panel.

Background

Smartphones and watches and their inbuilt sensors allow for the collection of a near to infinite amount of data about their owners. Taking advantage of these capabilities to improve disease characterisation and monitoring and to support treatment decisions in MS seems obvious but faces a number of challenges: Selection and validation of a comprehensive and meaningful set of tests, managing the immense amount of data and identifying the useful information, data privacy and ascertainment of long-term adherence.

Objectives

To assess systematically the feasibility of a comprehensive smartphone and smartwatch based set of digital biomarkers for disease monitoring in patients with MS (PwMS) and validate this tool against currently available state of the art clinical, imaging and body fluid assessments.

Methods

The dreams App is a software application including multiple biomarkers for each of the domains movement, dexterity, cognition and vision as well as questionnaires for fatigue and other patient reported outcomes. Compliance is enhanced through a gamification-approach. We are currently conducting a feasibility study with a group of PwMS and matched healthy controls to further evaluate the technical reliability of a larger set of digital biomarkers and select those best suited for the validation studies. Early next year, the first of two independent validation studies including 400 PwMS, recruited from participants in the Swiss MS cohort (SMSC) is planned to further validate the digital biomarkers through correlation with established standardized clinical, imaging and body fluid markers already implemented in the SMSC.

Results

Preliminary in-house reliability testing with healthy controls showed intra class correlation coefficients of >60% for the digital biomarkers included in the feasibility study and >80% for at least one in every domain. These results were derived through unguided repetitions over multi-day-timeframes and not optimal laboratory conditions in order to truthfully reflect future use.

Conclusions

With this program, we aim at establishing dreams as a novel smartphone-based comprehensive, modular, validated, independent and broadly accepted digital assessment tool for PwMS. Integrated into a data management and precision medicine based decision support system this assessment tool would improve every day management and allow for better assessment of new therapies in the setting of clinical trials.

Background

Astrocytes and microglial cells are now recognized as active players in contributing to the diffuse neuroaxonal damage associated with disease progression of multiple sclerosis (MS). The serum level of glial fibrillary acidic protein (GFAP), a biomarker for astrocytic activation, is increased in MS and associated with the disease progression and disability. Similarly, diffusion tensor imaging (DTI) parameters for microstructural changes in brain, including demyelination and axonal loss, associate with disability. The association between brain DTI parameters and serum GFAP has not been previously explored in MS.

Objectives

To get insights into DTI-measurable pathological correlates of elevated serum GFAP in the normal appearing white matter (NAWM) of MS.

Methods

A total of 62 MS patients with mean age of 49.4 years were included in the study. Study patients underwent DTI-MRI and blood sampling for GFAP determination by single molecule array (Simoa). MS patients were subdivided to GFAP(high) and GFAP(low) groups based on the median value of GFAP (97.7 pg/ml). Mean fractional anisotropy (FA) and mean (MD), axial (AD) and radial (RD) diffusivities were calculated within the NAWM and six segmented NAWM regions. The associations between the DTI parameters and GFAP levels were analyzed within the GFAP(high) and GFAP(low) subgroups using Spearman correlation analysis and multiple regression model with sex and disease modifying treatment (no, 1^st line or 2^nd line) as adjustments performed with the R statistical software (version 4.0.0).

Results

Elevated serum GFAP levels correlated significantly with decreased FA values within the entire, frontal, temporal and cingulate NAWM (R=-0.39, p=0.03; R=-0.42, p=0.02; R=-0.37; p=0.04 and R=-0.38, p=0.03) and increased MD and RD within the frontal NAWM (R=0.36, p=0.046 for both) in the GFAP(high) subgroup. Associations between higher GFAP and lower FA in frontal and cingulate NAWM were sustained in the multiple regression model corrected for confounding variables (standardized regression coefficient r = -0.29, p = 0.045 and r = -0.33, p = 0.025).

Conclusions

Our results give evidence that increased serum GFAP levels are associated with DTI-measurable micro-damage in the NAWM in MS. Our work supports the use of serum GFAP as a biomarker for MS pathology-related astrocytopathy and related diffuse white matter damage.

Background

Additional biomarkers reflecting disease activity and predicting severity of multiple sclerosis (MS) are urgently needed.

Objectives

To explore whether intrathecal immunoglobulin (Ig) M synthesis is associated with time from disease onset to first relapse, MS Severity Score (MSSS) and time to first initiation of high efficacy disease modifying treatments (DMT) in patients with relapsing MS in the Swiss Multiple Sclerosis Cohort study.

Methods

487patients were categorized by presence of CSF oligoclonal IgG bands (OCGB) and quantitative intrathecal IgG and IgM production (Intrathecal Fraction, IF). Treatments were classified according to "no therapy", "platform", "oral" and "high efficacy". Multivariable Cox proportional hazard models or a multivariable linear model, adjusted for relevant covariables, were used to assess time from disease onset to described endpoints and associations with the MSSS.

Results

OCGB were present in 89.3%, IgGIF in 66.3%, IgMIF in 26.9% and IgAIF in 11.9% of patients. Patients with IgMIF had a shorter interval from disease onset to first relapse (HR 1.887 [CI 1.181, 3.014], p<0.01) compared to those without OCGB and IgGIF and IgMIF. Quantitatively, patients with IgMIF above versus below the median had a 1.75- fold increased hazard of occurrence of a first relapse (HR 1.746 [CI 1.097, 2.781]; p=0.019). IgMIF positive patients had on average a 1.24 steps higher MSSS compared with those without any intrathecal Ig synthesis (estimate: 1.243 [CI 0.501,1.986], p<0.01), followed by patients with OCGB and quantitative production of IgGIF (estimate: 0.966 [CI 0.283, 1.650], p<0.01) and patients with only OCGB (estimate: 0.716 [CI -0.030, 1.461], p=0.060). Accordingly, patients with IgMIF production had a shorter interval to initiation of high efficacy DMT (HR 2.788 [CI 1.306, 5.951], p<0.01). Quantitatively, above versus below median IgMIF was associated with a 2.36-fold risk of escalation to a high efficacy DMT (HR 2.361 [CI 1.304, 4.277]; p<0.01).

Conclusions

In relapsing MS, presence of intrathecally produced IgM is associated with higher disease activity, more severe disease course and earlier use of high efficacy treatments. Intrathecally produced IgM may qualify as useful prognostic biomarker for therapeutic decision making in early stage of disease.

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

Neurofilament light chain (NfL) is a biomarker of neuroaxonal injury in multiple sclerosis (MS). Thalamic atrophy occurs early and may be a sensitive marker of overall brain damage. Ocrelizumab (OCR) reduced brain atrophy and NfL in patients with relapsing MS (RMS) and those with primary progressive MS (PPMS).

Objectives

To examine the independent impact of OCR and baseline (BL) NfL on thalamic volume (TV) and clinical progression in patients with PPMS and RMS, including those with RMS without acute BL activity (i.e. no gadolinium–enhancing [Gd+] lesions or relapse in the last 3 months).

Methods

Patients were from OPERA I/II (RMS, n=1,421) and ORATORIO (PPMS, n=596). Thalamic atrophy was calculated as annualized percentage TV change (PTVC) from Wk 24 to the end of controlled treatment (ORATORIO, Wk 120; OPERA I/II, Wk 96). OCR treatment (vs IFNβ-1a [RMS] or placebo [PPMS]) and log-transformed BL NfL were examined for associations with PTVC (linear regression) and 24-week confirmed disability progression (Cox regression) adjusting for BL demographic and disease characteristics.

Results

In patients with PPMS and RMS, OCR treatment (PTVC: +0.47% and +0.33%, respectively) and lower BL NfL (+0.20% and +0.33% per 2-fold lower NfL) independently associated with a smaller TV reduction (all p<0.005). Adjusting for BL NfL level, Gd+ lesion count, T2 lesion volume and BL disability, OCR still reduced disability progression on Expanded Disability Status Scale (EDSS) (PPMS, hazard ratio [HR]=0.73; RMS, HR=0.65; both p<0.05]), 9-Hole Peg Test (9HPT) (PPMS, HR=0.53, p=0.002; RMS, HR=0.52, p=0.059), Timed 25-Foot Walk (T25FW) (PPMS, HR=0.79, p=0.063), Symbol Digit Modalities Test (RMS, HR=0.54, p=0.002) and time to EDSS 6 (RMS, HR=0.42, p=0.009). In patients with PPMS, higher BL NfL was associated with worsening on 9HPT (HR=1.34 per 2-fold higher NfL), T25FW (HR=1.19) and time to EDSS 7 (HR=1.78) (all p<0.05). In patients with RMS without acute BL activity, higher BL NfL was associated with EDSS worsening (HR=1.49), progression independent of relapse activity (PIRA) (HR=1.61), 9HPT (HR=2.1) and time to EDSS 6 (HR=2.24) (all p<0.05).

Conclusions

Ocrelizumab treatment remained associated with reduced thalamic atrophy and clinical progression after adjusting for baseline NfL and other factors. Higher BL NfL was associated with increased rates of thalamic atrophy and clinical progression in patients with PPMS and those with RMS without acute disease activity.

Background

Blood neurofilament light chain (NfL) is a biomarker of neuroaxonal injury associated with acute disease activity and may be prognostic for disability progression in patients with multiple sclerosis (MS). Ocrelizumab (OCR) is an anti-CD20 monoclonal antibody indicated for relapsing MS (RMS) and primary progressive MS (PPMS).

Objectives

To assess the impact of OCR on blood NfL distribution in patients with RMS from the OPERA I and II trials and those with PPMS from ORATORIO.

Methods

Pretreatment and posttreatment NfL levels (measured using the SiMOA assay) with OCR vs interferon β-1a (OPERA I and II; n=1,421) or placebo (ORATORIO; n=596) were compared using geometric mean (GM) and GM ratios (GMR). Patients were stratified by presence/absence of acute disease activity at baseline (BL) (T1 gadolinium [Gd]-enhancing lesions and/or relapse in prior 3 months for RMS; T1 Gd-enhancing lesions for PPMS). Age-adjusted NfL distributions (using a linear model for log-NfL and age derived from a healthy donor [HD] cohort) at BL and after OCR were compared with HD using the Kolmogorov-Smirnov test.

Results

Significant reductions in NfL were observed 3 months after OCR initiation (RMS, GMR=0.80; PPMS, GMR=0.89) and sustained through the end of controlled treatment (RMS [96 weeks], GMR=0.56; PPMS [120 weeks], GMR=0.81; all p<0.0001). Age-adjusted BL serum NfL was elevated in patients with RMS disease activity (GM [95% CI]=12.7 [11.9–13.6] pg/mL) vs those without (5.5 [5.3–5.7] pg/mL) and HD (4.1 [3.9–4.4] pg/mL; all p<0.0001). In OCR-treated patients with RMS, GM [95% CI] serum NfL levels after 96 weeks (with activity at BL, 4.4 [4.2–4.6] pg/mL; without activity at BL, 4.1 [4.0–4.3] pg/mL) were comparable to HD (4.1 [3.9–4.4] pg/mL; all p>0.1). Age-adjusted BL plasma NfL was also elevated in PPMS patients with disease activity (GM [95% CI]=8.7 [7.5–10.1] pg/mL) vs those without (4.9 [4.6–5.2] pg/mL) and HD (3.1 [2.9–3.3] pg/mL; all p<0.0001). In OCR-treated patients with PPMS, GM [95% CI] plasma NfL levels after 120 weeks (with activity at BL, 4.6 [4.1–5.1] pg/mL; without activity at BL, 4.2 [4.0–4.4] pg/mL) were reduced from BL (all p<0.005) but remained elevated vs HD (all p<0.001).

Conclusions

NfL is highly elevated in patients with acute MS disease activity, and more subtle elevations are observed in RMS and PPMS patients without detectable disease activity. Ocrelizumab significantly reduces NfL in RMS and PPMS patients with and without detectable disease activity.

Background

Serum neurofilament light chain (sNfL) levels are a promising biomarker for quantifying neuro-axonal injury in multiple sclerosis (MS). Recent studies showed sNfL levels relate to disease activity and treatment response.

Objectives

To analyze the predictive capacity of baseline (BL) sNfL levels for disease outcomes in the 15-year BENEFIT study long-term follow-up

Methods

Monofactorial regression analyses were conducted on outcomes at Year 15, including sNfL age-adjusted percentiles (80^th, 90^th, 95^th, 97.5^th and 99^th; Disanto et al., 2017).

Further BL covariates included sex; age; lowest EDSS up to Month 6; mono/multifocal onset; presence of optic nerve, brainstem, or spinal cord lesions; Paced Auditory Serial Addition Test 3 (PASAT-3), Timed 25 Foot Walk (T25W), and 9 Hole PEG test (9HPT) scores; number/volume of hypointense T1, gadolinium-enhancing T1, and T2 lesions; cerebral volume; and initial treatment assignment. On-study covariates at Years 1, 2, and 5 were annualized relapse rate; EDSS change; PASAT-3, T25W, and 9HPT scores; annualized rate of new lesions; lesion number/volume; brain volume change; and relative duration of treatment. Covariates with p≤0.1 (at ≥2 time points for on-study covariates) were entered into multifactorial models.

We assessed the predictive capacity of BL sNfL levels for the following outcomes: EDSS ≥4, clinically silent disease, T2 lesion volume, and cerebral volume.

Results

Patients with sNfL values at screening (N=258) above the 90^th (n=176), 95^th (n=157), 97.5^th (n=149), and 99^th (n=129) percentiles (adjusted for other relevant covariates) had a significantly higher risk of EDSS≥4 at Year 15 for BL model (odds ratio 2.45 [95% CI: 1.05,5.68] p=0.0376; 2.60 [1.18,5.75] p=0.0181; 2.61 [1.20,5.66] p=0.0154; 2.47 [1.19,5.13] p=0.0150, for the 90^th, 95^th, 97.5^th and 99^th percentiles, respectively), and for on-study models at Year 1 (3.86 [1.16,12.78] p=0.0272; 3.38 [1.13,10.14] p=0.0296; 2.92 [1.02,8.35] p=0.0461; 2.98 [1.11,8.00] p=0.0305, respectively) and Year 2 (5.36 [1.26,22.85] p=0.0231; 4.88 [1.34,17.77] p=0.0163; 3.86 [1.18,12.66] p=0.0259; 3.34 [1.17,9.48] p=0.0237, respectively). Covariates that remained statistically significant with EDSS≥4 as the endpoint in most percentile models were lowest EDSS value up to Month 6 for BL and Year 1, and change in brain volume at Year 1, 2, and 5.

Conclusions

Findings in this unique long-term BENEFIT study suggest that higher sNfL values in early MS disease stages are independent predictors of long-term disability.

Background

BACKGROUND: Experimental, genetic and therapeutic studies suggest a role for natural killer (NK) cells in multiple sclerosis (MS). A study analysing the re-emergence of Th17 cells after autologous hematopoietic stem cell transplantation proposes that the relative presence of NK cells compared to CD4⁺ T cells is beneficial in MS, as it is associated with lower levels of Th17. As such, they propose that NK/T cell ratios may be used as a biomarker for therapeutic effect of stem cell transplantation. This ratio has not been investigated in the context of clinical outcome. Additionally, the subsets of NK cells and T cells have not been investigated in regards to this NK/T cell ratio.

Objectives

OBJECTIVES: To explore the relevance of NK cell / CD4⁺ T cell ratios in a cohort of MS patients treated with interferon beta by analysing NK cell subsets and T cell subsets. Additionally, to find the prognostic value of these ratios for disease activity in MS

Methods

METHODS: Baseline peripheral blood mononuclear cells of 50 relapsing remitting MS patients, participating in our vitamin D supplementation study (the SOLARIUM study), were isolated and analysed with flow cytometry for NK and T cell subsets. MS disease activity was quantified by assessment of the occurrence of new MRI-lesions, relapses, and by measuring mean plasma neurofilament light chain (NfL) levels at baseline and after 48 weeks follow-up.

Results

RESULTS: The proportion of NK cells correlated negatively with CD4⁺ T cells [R=-0.335 p=0.001] and IL17-A⁺CD4⁺ T cells [R=-0.203 p=0.043], which was mainly driven by the CD56^bright subset. Participants with MRI activity or relapses at 48 weeks follow-up displayed lower NK/ IL-17A⁺ CD4⁺ T cell ratios [p=0.025 and p=0.006, respectively]. The NK / IL-17A⁺CD4⁺ T cell ratio correlated negatively with NfL levels [R=-0.320 p=0.050]. Vitamin D supplementation did not affect these ratios.

Conclusions

CONCLUSIONS: Our data suggests a protective role of a relatively expanded NK cell compartment compared to the CD4⁺ T cell subset fractions in interferon beta-treated RRMS patients. Further research is required to confirm the use of the NK cell/CD4⁺ T cell ratio as prognostic biomarker for disease activity in MS.

Background

Serum neurofilament light chain (sNfL) and retinal optical coherence tomography (OCT) measurements have individually been shown to be promising biomarkers for future disease activity in multiple sclerosis (MS).

Objectives

To investigate the complementary value of sNfL and retinal OCT measurements for predicting disease activity in patients with early MS at a stable disease state.

Methods

We retrospectively screened patients with early MS or clinically isolated syndrome (CIS) from a prospective cohort study (Berlin CIS cohort). The baseline sNfL (single-molecule array (Simoa^TM) assay) were determined between 12 and 24 months after initial disease onset. Inclusion criteria were the availability of baseline sNfL, OCT measurements, clinical and MRI follow-up data (new relapses, expanded disability status scale (EDSS), new T2 lesions, composing the no evidence of disease activity (NEDA-3) criteria) over a period of at least 365 days. Exclusion criteria were concomitant eye diseases interfering with OCT and a relapse within 120 days before baseline visit. For Cox regression hazard models, patients were grouped with regards to their sNfL level (abnormal/normal: ≥/< 95th percentile of age-matched reference value) and their peripapillary retinal nerve fiber layer (pRNFL: >/≤ 100 µm) and ganglion cell and inner plexiform layer (GCIP: >/≤ 1.99 mm³) in non-optic neuritis eyes. Analysis was censored after 760 days.

Results

We included 78 patients (50 females, age: 36.4 ± 7.6 years) with a median follow-up of 728 days (range: 709 – 751 days). Patients with abnormal sNfL at baseline showed a significantly higher risk for developing a new relapse (Hazard Ratio (HR): 3.33, 95% confidence interval (CI): 1.43 – 7.71, p = 0.003), a new lesion (HR: 2.64, CI: 1.35 – 5.18, p = 0.003) and violating NEDA-3 (HR: 3.22, CI: 1.73 – 6.01. p < 0.001). Patients with both thinner pRNFL and abnormal sNfL value had a greater risk for developing a new relapse (HR: 8.12, CI: 2.17 – 30.46, p = 0.002) and violating NEDA-3 criteria (HR: 4.28, CI: 1.81 – 10.14, p < 0.001) than patients with only one of the risk factors. Meanwhile, patients with thinner GCIP and abnormal sNfL not only yielded greater risk for new relapse (HR: 6.51, CI 2.06 – 20.63, p = 0.001) and NEDA-3 violation (HR: 4.48, CI: 2.11 – 9.50, p < 0.001), but also for new lesion (HR: 3.11, CI: 1.42 – 6.80, p = 0.004).

Conclusions

In patients with early MS, presence of both abnormal sNfL and OCT measurements may be a stronger risk factor for future disease activity than presence of each risk factor alone.

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

Elevated levels of plasma neurofilament light chain (pNfL) is associated with increased disease activity, physical disability and reduced treatment response in persons with multiple sclerosis (MS). However, the association between environmental exposures such as cigarette smoking and pNfL levels is not clear.

Objectives

To investigate the association between cigarette smoking, as one of the most prominent environmental factor associated with MS disease activity, and pNfL-levels in MS.

Methods

This is a retrospective population-based cohort study. Blood samples from incident MS cases were collected at time of diagnosis (from 2001). Concentrations of pNfL were determined using antibodies from UmanDiagnostics and the high-sensitive Single Molecule Array (SimoaTM) NF-light® Advantage kit. We assessed the impact of self-reported cigarette smoking habits at time of sampling on age-stratified pNfL levels above 80^th, 95^th, and 99^th of non-MS controls' percentiles (>C80, >C95, and >C99).

Results

pNfL levels were measured in 2881 MS cases with smoking history of which 320 (11.1%) were current regular smokers and 828 (28.7%) were past regular smokers (median years since quitting 6; IQR 1 to 14). Current smoking was associated with significantly increased odds ratios (OR) of having pNfL-levels >C80, >C95 and >C99 with OR ranging from 1.27 (95% CI: 0.96-1.68) to 1.70 (95% CI: 1.24-2.33) comparing current smokers to never smokers and 1.44 (95% CI: 1.06-1.94) to 1.6 (95% CI: 1.12-2.27) comparing current smokers to past smokers. The OR of having pNfL-levels >C80, >C95 and >C99 in past smokers who quitted 6 to 10 years ago, compared to current smokers, ranged from 0.6 (95% CI: 0.39-0.92) to 0.55 (95% CI: 0.30-0.95), and from 0.62 (95% CI: 0.43-0.89) to 0.53 (95% CI: 0.31-0.87) in those with >10 years since quitting smoking. Although decreased, the ORs were not significant among those quitting smoking 1 to 5 years before sampling (P>0.05).

Conclusions

Current regular smoking is associated with significantly increased risk of displaying high pNfL levels in MS patients, which argue for a negative effect on disease activity. In contrast, there was a beneficial effect of quitting smoking that increased with time since stopping. Our findings support the rational for life style counselling in MS.

Background

Serum neurofilament light chain (sNfL) levels reflect only neuro-axonal injury that took place within 3-6 months prior to the date of sampling. Therefore, the frequency of assessment of sNfL levels for monitoring of disease activity warrants further investigation.

Objectives

To determine differences in accuracy of sNfL levels to detect radiological disease activity during the preceding 6 versus 12 months of follow-up.

Methods

This observational study included 148 patients with early relapsing-remitting multiple sclerosis (MS) from the SET cohort. Based on brain MRI performed at 0, 6 and 12 months, we assessed the ability of categorized sNfL measured at 12 months to reflect the presence of combined unique active lesions, defined as new/enlarging lesion compared with MRI performed in the previous 6 versus 12 months or contrast-enhancing lesion (e.g., active lesions).

Results

Together, 91% (95% CI=85-98%) of patients with ≥1 active lesion during the last 6 months and 84% (95% CI=77-92%) of patients with ≥1 active lesion during the last 12 months had sNfL≥30^th percentile. Among the patients with sNfL<30^th percentile, 14 (33.3%) developed ≥1 active lesion during the last 12 months, but only 6 (14.3%) developed ≥1 active lesion during the last 6 months. Among patients with sNfL<30^th percentile, 6 (14.3%) developed ≥2 active lesions during the last 12 months, but only 2 (4.8%) developed ≥2 active lesions during the last 6 months.

Conclusions

Low levels of sNfL better identified MS patients with the absence of recent radiological disease activity during the previous 6 than the previous 12 months. In the future, assessment of sNfL at least every 6 months may substitute the need for annual brain MRI monitoring to exclude brain lesion activity in clinically stable patients with low sNfL levels.

Background

Background: The envelope protein of the human endogenous retrovirus type W (HERV-W ENV) is expressed in chronic active MS lesions. Preclinical models have shown that HERV-W ENV activates microglia, prevents maturation of oligodendrocyte precursor cells, and leads to neuronal death. Following the effects of a B-cell depleting, anti-inflammatory therapy, rituximab (RTX), with temelimab (TML), a humanized, IgG4-κ monoclonal antibody against HERV-W ENV represents a novel therapeutic approach against neurodegenerative features of MS.

Objectives

Objective: To present safety preclinical results on the interaction of RTX and TML, and the trial design of the ProTEct-MS study.

Methods

Design/Methods: Interactions between RTX and TML were studied in vitro in high density-peripheral blood mononuclear cells (PBMCs) and ex-vivo in a whole blood loop system from fresh human blood.

ProTEct-MS is a randomized, double-blind, placebo controlled, parallel group study. Enrolment commenced in 2020/6 and will be completed in 2020/12. Patients with RMS (2017 McDonald criteria) (N=40) being previously treated for ³12 months with RTX are randomized (1:1:1:1) to monthly iv TML (18, 36 or 54mg/kg) and placebo for 48 weeks.

Eligibility criteria: age 18-55 yrs, Expanded Disability Status Scale (EDSS) of 2.5-5.5 at screening; clinical worsening in ³1 neurological domain as assessed by EDSS, 6MWT or T25FW, or cognitive functioning as assessed by SDMT over the last year.

Primary objective: assessment of safety and tolerability of TML

Secondary outcome measures: MRI: change of brain atrophy, lesion volume and magnetization transfer ratio

Results

Results: Co-administration of TML with RTX was overall comparable to vehicle for all blood parameters assessed including cytokine levels of all five donors tested in both in vitro and ex-vivo assays. Co-administration of TML with RTX did not affect the functionality profile of either compound. By September 2020, 25% of patients are expected to be randomized, providing baseline clinical and MRI characteristics.

Conclusions

Conclusions: Preclinical safety experiments of the drug combination showed no evidence against the use of TML following RTX in humans. ProTEct-MS study patients represent a RMS cohort with progression in absence of relapse activity (PIRA,) i.e. whose present clinical condition is stable under RTX therapy, enabling TML's effects on attenuating mechanisms of progression to be measured without interference by acute inflammatory activity.

Background

Ocrelizumab is the first drug approved as disease modifying treatment for primary progressive (PP) multiple sclerosis (MS). As a humanized monoclonal antibody targeting CD20 cells, it is widely known that ocrelizumab treatment results in B cells depletion, but less is known about the effects of this drug in other blood leukocyte subsets of PPMS patients.

Objectives

To explore the changes induced by ocrelizumab in blood immune cells of PPMS patients to further understand their effects in the abnormal inflammatory response.

Methods

Multi-centre prospective longitudinal study including fifty‐three PPMS patients who initiated ocrelizumab treatment. Effector, memory, and regulatory cells were analyzed by flow cytometry at baseline and after 6 months of treatment. To assess differences between baseline and after 6 months, Wilcoxon matched paired tests were used and p values were corrected using Bonferroni test.

Results

Ocrelizumab decreased numbers of naïve and memory B cells (p<0.0001) and those of B cells producing interleukin (IL)-6, IL-10, granulocyte-macrophage colony-stimulating factor and tumor necrosis factor-alpha (p<0.0001 in all cases). A reduction of CD20+ T cell numbers (p=0.02) and percentages (p<0.0001) was also observed. We also detected a clear remodelation of the T cell compartment characterized by relative increases of the naïve/effector ratio in CD4+ (p=0.002) and CD8+ (p=0.002) T cells, and relative decreases of CD4+ (p=0.03) and CD8+ (p=0.004) T cells producing interferon-gamma. Total monocyte numbers increased (p=0.002), with no changes in those producing inflammatory cytokines. All these changes resulted in a reduction of serum neurofilament light chain (sNfL) levels (p=0.009).

Conclusions

Effector B cell depletion by ocrelizumab treatment induces changes in the T cell response of PPMS patients towards a low inflammatory profile. This resulted in a decrease of sNfL levels.

Background

Accurate determination of relapses in multiple sclerosis (MS) is important for subtype classification and therapeutic decisions. However, there are currently no validated bio-fluid markers of relapses.

Objectives

To determine if metabolic perturbations are present during relapses, and if so, to identify candidate metabolite biomarkers and evaluate their discriminatory value both at group and individual levels, in comparison with serum neurofilament-light (NfL).

Methods

Global and targeted serum high resolution ¹H nuclear magnetic resonance metabolomics and serum NfL (Simoa® assay) were performed on 4 groups of relapsing-remitting MS (RRMS) patients; (1) in relapses (in-R), (2) last relapse (LR) ≥1 month (M) to <6 M ago, (3) LR ≥6 M to <24 M ago, and (4) LR ≥24 M ago. Supervised multivariate analyses were used to determine metabolic differences between patient groups.

Results

Two hundred and one RRMS patients were recruited; in-R (n=38), LR 1–6 M (n=28), LR 6–24 M (n=34), LR ≥24 M (n=101). The global metabolic profile of in-R was significantly perturbed compared to LR ≥24 M (mean predictive accuracy ± SD, 62.6 ± 4.8% vs. 50.9 ± 8.2%; p <0.0001). Identified discriminatory metabolites were quantified, when possible, using targeted metabolomics. Lysine (high in-R), asparagine (high), isoleucine (low) and leucine (low) were shortlisted as potential metabolite biomarkers. One-way ANOVA of these metabolites showed significant differences across the 4 patient groups, with a clear trend (increasing or decreasing) with time away from relapse. Multivariable receiver operating characteristics (ROC) analysis of these 4 metabolites in discriminating in-R vs. LR ≥24 months showed an area under the curve (AUC) of 0.758, while serum NfL had an AUC of 0.575. Within individual patients (n=9) with paired relapse-remission samples (remission sample taken within 6 months of relapse), all 4 metabolites were significantly different in relapse and in remission, with directions consistent with that observed at group level, while serum NfL was not significant. Multivariable ROC of the 4 metabolites showed an AUC of 0.911. At group level, lysine and asparagine were higher in patients with gadolinium enhancing lesions in the last 1 year prior to sampling. No potential confounders were identified on further analyses, notably; none of in-R was on steroids at blood sampling.

Conclusions

Metabolomics identify perturbations in metabolites relating to energy deficiency and immune activation in relapses, and the use of these metabolites, singly or in combination, are useful in identifying relapses, both at group and individual level.

Background

Myelin water imaging (MWI) and neurite orientation dispersion and density imaging (NODDI) provide sensitive surrogate markers of myelin and axonal content in lesions and normal-appearing tissue. However, to date, there is scarce information about the relationship of these measures with (i) disability; and (ii) the axonal damage specific biomarker serum neurofilament light chain (sNfL).

Objectives

To explore the correlation of MWI and NODDI measures in MS lesions and in normal-appearing (NA) brain tissue with disability and sNfL.

Methods

Ninety-one MS patients (62 relapsing-remitting MS-RRMS and 29 progressive MS-PMS) underwent MWI and NODDI. Mean myelin water fraction (MWF) and neurite density index (NDI) were extracted in white matter lesions (WMLs), cortical lesions (CLs), NA white matter (NAWM) and cortical NA gray matter (CNAGM). For sNfL, a logarithmic transformation was applied to comply with normality assumption. Correlation studies between MRI measures, sNfL and EDSS were performed using linear models, with age and gender as covariates. The models were performed for the whole sample and for patients with clinical deficits only (EDSS >1).

Results

MWF and NDI did not correlate with EDSS when the entire cohort was considered (P>0.05). However, for those patients with clinical deficits (EDSS> 1), NDI in WMLs was associated with EDSS (NDI: P<0.01, beta=-10.00; N=74). We also found that MWF and NDI in WMLs were related to sNfL (MWF: P<0.01, beta=0.13; NDI: P<0.01, beta=-3.60). Again, this correlation was stronger in patients with EDSS>1 (MWF: P<0.01, beta=0.13; NDI: P <0.01, beta=-3.60).

Conclusions

Imaging surrogate markers of myelin and axon pathology in WML – and not in CLs and NA tissues - are correlated with disability and sNfL. Interestingly, associations between those imaging markers and disability/sNFL were more evident in patients with clinical deficits as compared to those without neurological deficits.

Background

Advanced diffusion-weighted MRI (DW-MRI) sequences, in combination with biophysical models, provide unprecedented information on the microstructural properties of both healthy and pathological brain tissue.

Nevertheless, it is nowadays challenging to identify the most accurate biophysical model to describe focal microstructural pathology in multiple sclerosis (MS) patients, due to the lack of appropriate comparative studies.

Objectives

To investigate the specificity and sensitivity of 124 independent features derived from 20 diffusion microstructural models to differentiate specific features of tissue alterations in white matter (WM) lesions compared to the surrounding normal-appearing WM (NAWM).

Methods

The study included 102 MS patients: RRMS: 66%, SPMS: 18%, PPMS: 16%, mean age 46±14; female 64%, disease duration 12.16±18.18 years, median Expanded Disability Status Scale (EDSS): 2.5.

DW-MRI data were acquired with 1.8mm isotropic resolution isotropic and with the b-values [0, 700, 1000, 2000, 3000] s/mm².

Lesion masks were generated with a deep learning network algorithm and manually corrected if required. Voxels of NAWM tissue were randomly chosen outside the lesion masks.

The following microstructural models were applied: DTI, Non-parametric DTI, DKI, Ball and Stick, Ball and Sticks, Ball and Rockets, NODDI-Watson, AMICO-NODDI, NODDI-Bingham, SMT-NODDI, NODDIDA, SMT, MCMDI, CHARMED, IVIM, sIVIM, Microstructure Fingerprinting, Microstructure Bayesian, DIAMOND, and DIAMOND isotropic-restricted.

The classification was performed using logistic regression on 300’000 voxels, equally divided in lesion and NAWM voxels. Features were scored according to the Area Under the Curve (AUC), sensitivity, and specificity.

Results

The intra-axonal signal fraction of the Microstructure Bayesian approach scored maximum with AUC=0.87, for threshold=0.5 sensitivity=0.79, sensitivity=0.83. AUC = 0.86 were attributed to the intra-axonal signal fraction of Ball and rockets, NODDI-Watson, AMICO-NODDI, NODDI-Bingham, SMT-NODDI and the extra-axonal perpendicular signal fraction of the Microstructure Bayesian approach. Low AUC scores (<0.75) were achieved by DTI and parameters not related to signal fractions, e.g. orientation dispersion.

Conclusions

Among available microstructural models, the Microstructure Bayesian appeared to best differentiate voxels with microstructural damage in WM lesions compared to NAWM. Very similar, albeit slightly lower accuracy, was achieved by NODDI-based models. In general, models with estimates intra-axonal signal fraction tend to perform better in this type of classification, showing that intra-axonal component may be the dominant factor in distinguishing the two types of tissue. Further analysis will explore the advantage of including combinations of independent features.

Background

LeMan-PV is a prototype that performs cross-sectional and longitudinal detection of Multiple Sclerosis (MS) lesions, which has been validated on conventional (cMRI) and advanced magnetic resonance imaging at 3T (Fartaria et al. 2019). Since this software provides a report that is available shortly after image acquisition, it may be ideal as clinical decision-support tool.

Objectives

To assess LeMan-PV as clinical decision-support tool in a monocentric real-world cMRI dataset from the Swiss Multiple Sclerosis Cohort.

Methods

262 MS patients underwent cMRI at Basel University Hospital in a mean of 3.5 follow-up sessions, with an average of 399 days between two consecutive sessions. cMRI sequences were acquired at 1.5T and 3T in 725 and 195 sessions, respectively. Cross-sectional and longitudinal MS lesions segmentation (i.e. identification of new and enlarging lesions - NLs, ELs) was performed using the LeMAN-PV prototype software. An expert neuroradiologist performed a radiological reading of the number of NLs and ELs in the most recent acquisition by comparing it to the previous one (ground truth, GT), considering only lesions with a diameter larger than 3 mm. The minimum volume thresholds to identify an NL and an EL were chosen by minimizing the patient-wise error between the automated count and the expert ground truth. Two scenarios were evaluated by first assuming disease activity if one or more EL were present, and second by considering activity if NL were present in the new acquisition.

Results

The volume thresholds chosen were 11 and 12 mm³ for ELs and NLs, respectively. For those, LeMan-PV detected 11% more of both ELs and NLs than the neuroradiologist. In the patient-wise evaluation of cases with both sessions acquired at 1.5T (70%), LeMan-PV showed sensitivities of 93% and 78% and specificities of 62% and 43% when evaluating ELs and NLs. For the 3T pairs of sessions (8%), values were 68% and 72% for ELs and 73% and 68% for NLs. Finally, for cases with a first acquisition at 1.5T and a second at 3T (22%), values were 76% and 73% for ELs and 71% and 65% for NLs.

Conclusions

The count of new and enlarging MS lesions using LeMan-PV were close to the one performed by an expert neuroradiologist; the software performed better when assessing disease activity via detection of enlarging lesions rather than by identifying new lesions. More 3T data is being currently collected at 3T to provide a size-matched inter-scanner comparison.

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

Gadolinium (Gd)-based contrast agents are widely used to assess disease activity and treatment response by MRI in multiple sclerosis (MS). There is, however, increasing concern about their safety as their repeated administration may lead to brain parenchymal accumulation, while preclinical models suggest that they induce mitochondrial toxicity and neuronal cell death. Moreover, recent reports have demonstrated that three-dimensional (3D) T2-weighted Fluid-Attenuated-Inversion-Recovery (FLAIR) is highly sensitive in detecting new or enlarging MS lesions.

Objectives

To explore whether the presence of contrast enhancing lesions (CEL) based on Gd injection is more sensitive in detecting lesional activity in clinically stable MS patients in comparison to the analysis of new or enlarging MS lesions by 3D FLAIR.

Methods

MS patients being part of the observational, multicenter Swiss Multiple Sclerosis Cohort Study (SMSC) with contrast enhanced T1-weighted (T1w) images were included. Clinical stability was defined as no relapse and no Expanded Disability Status Scale (EDSS) increase during at least twelve months prior to MRI. Presence of CEL was assessed on contrast enhanced T1w images. Presence of new or enlarging T2w lesions was assessed manually on 3D FLAIR in an independent analysis by a different investigator in clinically stable MS patients presenting with CEL.

Results

3930 MRI scans (3.0 Tesla n=1497 (38%)) in 1057 participants (685 women, median age 42.0 years, 941 with relapsing MS, 116 with progressive MS, median EDSS 2.0 (range 1.5-3.5), median disease duration 7.4 years) were included.

Of 2620 MRI scans (66.7%) acquired in clinically stable conditions 46 (1.8%) demonstrated CEL. In all of these, new or enlarging T2w lesions were detectable by 3D FLAIR when a previous MRI was available for comparison (previous MRI available in 29/46; median number of new or enlarging T2w lesions: 3 (range 1-41, total number 176); median number of CEL: 1 (range 1-4, total number 47)).

Conclusions

In our large cohort from clinical practice, the assessment of new or enlarging lesions by 3D FLAIR was equally sensitive as the quantification of CEL to detect disease activity in clinically stable MS patients, challenging current practice of the use of Gd-enhanced MRI for monitoring of MS in clinical routine.

Background

Advanced diffusion-weighted MRI (DW-MRI) sequences, in combination with biophysical models, provide new information on the microstructural properties of the tissue.

Objectives

To investigate the differences in intra-axonal signal fraction (IASF) between perilesional normal-appearing white matter (pl-NAWM), white matter lesions (WML) without (rim-) and with paramagnetic rim (rim+) comparing eight biophysical diffusion models.

Methods

The study included 102 MS patients: RRMS: 66%, SPMS: 18%, PPMS: 16%, mean age 46±14; female 64%, disease duration 12.16±18.18 yrs, median EDSS: 2.5.

DW-MRI data were acquired with 1.8mm isotropic resolution and b-values [0, 700, 1000, 2000, 3000] s/mm².

Lesion masks were generated with a deep-learning-based method and manually corrected if required; pl-NAWM was defined as a region of 3-voxels around each WML; 225 paramagnetic rim lesions were manually identified based on 3D EPI and 2330 were labelled as rim-.

The following microstructural models were applied: Ball and Stick, Ball and Rockets, AMICO-NODDI, SMT-NODDI, MCMDI, NODDIDA, CHARMED, Microstructure Bayesian approach.

Delta (WML - pl-NAWM) was calculated for each WML, and one-side Mann Whitney U was used to compare the delta between models, followed by Bonferroni to correct for multiple testing.

Mean difference and Cohen's d was used to assess differences between lesions with extensive axonal damage (rim+) and other WML (rim-).

Results

All models applied in this study reported low IASF in rim+ WML, medium IASF in rim- WML and relatively high IASF in pl-NAWM. However, a broad spectrum of IASF values was identified from the different models: relatively simple models such as Ball and Stick and CHARMED, showed low delta IASF within lesions, while MCMDI models reported the highest significant difference compared to other models (p<0.0001). The comparison between WML and pl-NAWM mean IASF across models showed that MCDMI exhibited the highest difference (mean 0.13, Cohen’s d 1.34). AMICO-NODDI and SMT-NODDI showed close results (mean difference 0.12/0.12 and Cohen’s d 1.46/1.51).

The models best discriminating IASF between rim+ and rim- lesions were MCMDI and NODIDDA (mean 0.08/0.07, Cohen’s d -0.69/-0.70).

Conclusions

We compared eight WM diffusion models for assessment of intralesional axonal damage in MS patients. The comparison between WML and pl-NAWM showed that robustness of the method, identified with SMT-based and NODDI-based models, it is crucial. For the comparison between lesions with a high level of damage (rim +) and other WML, the diffusivity estimation appeared to play an important role. The method which appeared both robust and able to estimate the diffusivity of the tissue was MCMDI, which performed best in both cases.

Background

Neuromyelitis optica spectrum disease (NMOSD) and multiple sclerosis (MS) have a different pathophysiology. Accumulating evidence suggests that the choroid plexus plays a pivotal role in the pathogenesis of MS. However, MRI data comparing the choroid plexus volume between MS and NMOSD are scarce.

Objectives

To compare the choroid plexus volume in MS vs. NMOSD in vivo using high-resolution 3D MRI data. Migraine patients and healthy individuals served as control groups.

Methods

We included 95 MS patients [45% secondary progressive (SP); mean age 51.0±11.5 years; disease duration 20.8±10.4 years, 62% female; median Expanded Disability Status Scale (EDSS) 4.0], 43 NMOSD patients [28/43 anti-aquaporin 4 antibody positive; 11/43 anti-myelin oligodendrocyte glycoprotein antibody positive; 87% female; mean age 50.0±13.8 years; disease duration 6.8±7.3 years, median EDSS 3.0], 38 migraine patients [mean age 39±13 years, 79% female; 15/38 migraine with aura] and 65 healthy individuals [HCs, mean age 41±17 years, 48% female]. The choroid plexus of the lateral ventricles and T2-weighted (T2w) white matter lesions (WMLs) were segmented fully automated on T1-weighted (T1w) magnetization-prepared rapid gradient echo (MPRAGE) images and fluid attenuated inversion recovery sequences (FLAIR, voxel size of both sequences 1x1x1 mm³), respectively, using a supervised deep learning algorithm (multi-dimensional gated recurrent units). Total intracranial volume (TIV) and lateral ventricle volumes were assessed fully automated using Freesurfer. All outputs were reviewed and manually corrected (if necessary) using 3D-Slicer by trained raters who were blinded to the clinical information. Group differences were analyzed using multivariable generalized linear models (GLMs) adjusted for age, gender, TIV and lateral ventricle volume. Cohens’ d was used to calculate the standardized difference between the respective groups. Given p-values are adjusted for multiple comparisons (Bonferroni).

Results

Mean choroid plexus was larger in MS compared to NMOSD (1907±455 vs. 1467±408 µl; p<0.001, d=0.86), HCs (1663±424 µl; p=0.007, d=1.17) and migraine (1527±366 µl; p=0.02, d=0.72). There was no statistical difference in the choroid plexus volume between NMOSD, migraine and HCs. The choroid plexus was marginally larger in RRMS than SPMS (1959±482 vs. 1875±476 µl; p=0.28; d=0.17) and in untreated MS patients compared to MS patients on disease modifying therapy (2111±382 vs. 1876±459 µl; p=0.36). However, these differences did not reach statistical significance after correction for multiple comparisons. There was no association between the choroid plexus volume and total T2w WML volume in MS.

Conclusions

Patients with MS have larger choroid plexus than HCs, migraine and NMOSD patients. Further studies are warranted to investigate the respective roles of the choroid plexus in the pathogenesis of MS and NMOSD.

Abstract

Neurofilaments: towards application in clinical practice

1. Do neurofilaments predict MS disease course?

Mark Freedman

3. Quantifying therapy response in MS by neurofilaments?

Jens Kuhle

3. Neurofilament applications outside the MS field

Roberto Furlan

Background

In the ASCLEPIOS I/II trials, ofatumumab significantly lowered serum neurofilament light (sNfL) levels, a marker of disease activity and treatment response, in the first assessment at month 3 and at all subsequent visits versus teriflunomide.

Objectives

To investigate the prognostic value of baseline sNfL for on-study disease activity and worsening in patients with relapsing MS, particularly in newly diagnosed, treatment-naïve patients.

Methods

Patients (pooled N=1882) were randomized to ofatumumab or teriflunomide, receiving treatment for up to 30 months. Patients were stratified by median baseline sNfL levels. We assessed annual on-study T2 lesion formation and brain volume loss (BVL, Jacobian integration) by sNfL category in all patients and in the subgroup of newly diagnosed within 3 year of screening without prior disease-modifying treatment (representing natural course of sNfL and disease at baseline) at month 24 or end of study. The annualized rate of new or enlarging T2 (neT2) lesions in year-2 versus year-1 was assessed in all patients by sNfL category (negative binomial model with time [in year] as offset).

Results

Patients with high sNfL (>median) levels at baseline developed more neT2 lesions per year on study than patients with low (≤median) sNfL levels (adjusted mean rate: ofatumumab: 0.95 vs 0.39, relative increase 143%, p<0.001; teriflunomide 5.28 vs 3.02, relative increase 74.5%, p<0.001). The prognostic value of baseline sNfL persists for year-2 (high vs low, ofatumumab: 0.09 vs 0.06, 64.5%, p=0.124; teriflunomide 4.53 vs 3.12, 45.6%, p=0.003. A single sNfL assessment at baseline had no prognostic value for on-study relapses and disability worsening. Patients with high baseline sNfL had higher annualized rate of BVL than patients with low sNfL (ofatumumab: 0.32% vs 0.23%, relative difference 37.3%, p=0.045; teriflunomide: 0.43% vs 0.29%, relative difference 49.4%, p<0.001). The results were consistent in the subgroup of newly diagnosed, treatment-naïve patients. The relative treatment effect of ofatumumab versus teriflunomide was similar across all measures in both the high and low sNfL groups.

Conclusions

Baseline sNfL levels were prognostic for on-study lesion formation and BVL for at least 2 years, in all patients and in the subgroup of newly diagnosed, treatment-naïve patients. sNfL levels can supplement clinical assessments and help identify patients at high risk for future disease activity.

Background

Quantification of the activity and progression of multiple sclerosis (MS) is an important tool for research on MS as well as its clinical treatment. Currently, disease activity and progression assessments rely on qualitative clinical evaluations or the acquisition of radiographic data such as magnetic resonance imaging (MRI).

Objectives

Quantifying MS disease activity (DA) and progression (DP) instead through the use of blood biomarkers would provide a significant reduction in barriers to such testing (e.g. monetary cost, time and specialized personnel requirements, invasiveness, operational difficulty, etc.). The use of an ensemble of proteins representing various biological pathways involved in MS pathophysiology would also provide useful insights into this complex and heterogeneous disease.

Methods

We investigated proteomic biomarkers associated with different levels of MS DA and DP using 205 blood serum samples from 88 patients (University Hospital Basel), extracting protein levels using Proximity Extension Assays (PEA) from Olink^TM. We then conducted a focused statistical analysis on 21 proteins that were selected for a custom MS assay panel development project based on their association with endpoints in previous studies. We corrected these protein levels using clinical data, including: age, sex, disease duration, age of the bio-banked sample, and medication status. We then compared protein levels to five different radiographic and clinical endpoints.

– Primary Endpoint: Gadolinium (Gd) enhanced lesion count

– Secondary Endpoints: T2 lesion volume, Expanded Disability Status Scale (EDSS) score, Clinically Defined Relapse Status, and Annualized Relapse Rate (ARR)

Results

In this report, we examine the univariate performance of selected proteins on the prediction of all five endpoints, comparing it to that of several multivariate machine learning techniques. We draw distinctions between the highest performing models for each endpoint and draw connections to the underlying biology governing MS activity and progression.

Conclusions

We found significant improvements in predictive power from the use of multivariate models in comparison to even the highest performing univariate techniques. The samples analyzed in this study will be re-assayed for validation purposes alongside additional cohorts in the forthcoming 21-plex custom MS proteomic assay panel.

Background

Serum neurofilament light chain (sNfL) levels are a promising biomarker for quantifying neuro-axonal injury in multiple sclerosis (MS). Recent studies showed sNfL levels relate to disease activity and treatment response.

Objectives

To analyze the predictive capacity of baseline (BL) sNfL levels for disease outcomes in the 15-year BENEFIT study long-term follow-up

Methods

Monofactorial regression analyses were conducted on outcomes at Year 15, including sNfL age-adjusted percentiles (80^th, 90^th, 95^th, 97.5^th and 99^th; Disanto et al., 2017).

Further BL covariates included sex; age; lowest EDSS up to Month 6; mono/multifocal onset; presence of optic nerve, brainstem, or spinal cord lesions; Paced Auditory Serial Addition Test 3 (PASAT-3), Timed 25 Foot Walk (T25W), and 9 Hole PEG test (9HPT) scores; number/volume of hypointense T1, gadolinium-enhancing T1, and T2 lesions; cerebral volume; and initial treatment assignment. On-study covariates at Years 1, 2, and 5 were annualized relapse rate; EDSS change; PASAT-3, T25W, and 9HPT scores; annualized rate of new lesions; lesion number/volume; brain volume change; and relative duration of treatment. Covariates with p≤0.1 (at ≥2 time points for on-study covariates) were entered into multifactorial models.

We assessed the predictive capacity of BL sNfL levels for the following outcomes: EDSS ≥4, clinically silent disease, T2 lesion volume, and cerebral volume.

Results

Patients with sNfL values at screening (N=258) above the 90^th (n=176), 95^th (n=157), 97.5^th (n=149), and 99^th (n=129) percentiles (adjusted for other relevant covariates) had a significantly higher risk of EDSS≥4 at Year 15 for BL model (odds ratio 2.45 [95% CI: 1.05,5.68] p=0.0376; 2.60 [1.18,5.75] p=0.0181; 2.61 [1.20,5.66] p=0.0154; 2.47 [1.19,5.13] p=0.0150, for the 90^th, 95^th, 97.5^th and 99^th percentiles, respectively), and for on-study models at Year 1 (3.86 [1.16,12.78] p=0.0272; 3.38 [1.13,10.14] p=0.0296; 2.92 [1.02,8.35] p=0.0461; 2.98 [1.11,8.00] p=0.0305, respectively) and Year 2 (5.36 [1.26,22.85] p=0.0231; 4.88 [1.34,17.77] p=0.0163; 3.86 [1.18,12.66] p=0.0259; 3.34 [1.17,9.48] p=0.0237, respectively). Covariates that remained statistically significant with EDSS≥4 as the endpoint in most percentile models were lowest EDSS value up to Month 6 for BL and Year 1, and change in brain volume at Year 1, 2, and 5.

Conclusions

Findings in this unique long-term BENEFIT study suggest that higher sNfL values in early MS disease stages are independent predictors of long-term disability.

Abstract

Neurofilaments: towards application in clinical practice

1. Do neurofilaments predict MS disease course?

Mark Freedman

3. Quantifying therapy response in MS by neurofilaments?

Jens Kuhle

3. Neurofilament applications outside the MS field

Roberto Furlan

Abstract

Neurofilaments: towards application in clinical practice

1. Do neurofilaments predict MS disease course?

Mark Freedman

3. Quantifying therapy response in MS by neurofilaments?

Jens Kuhle

3. Neurofilament applications outside the MS field

Roberto Furlan