Objective To assess whether chronic white matter inflammation in patients with multiple sclerosis (MS) as detected in vivo by paramagnetic rim MRI lesions (PRLs) is associated with higher serum neurofilament light chain (sNfL) levels, a marker of neuroaxonal damage. Methods In 118 patients with MS with no gadolinium-enhancing lesions or recent relapses, we analyzed 3D-submillimeter phase MRI and sNfL levels. Histopathologic evaluation was performed in 25 MS lesions from 20 additional autopsy MS cases. Results In univariable analyses, participants with ≥2 PRLs (n = 43) compared to those with ≤1 PRL (n = 75) had higher age-adjusted sNfL percentiles (median, 91 and 68; p < 0.001) and higher Multiple Sclerosis Severity Scale scores (MSSS median, 4.3 and 2.4; p = 0.003). In multivariable analyses, sNfL percentile levels were higher in PRLs ≥2 cases (β_add, 16.3; 95% confidence interval [CI], 4.6–28.0; p < 0.01), whereas disease-modifying treatment (DMT), Expanded Disability Status Scale (EDSS) score, and T2 lesion load did not affect sNfL. In a similar model, sNfL percentile levels were highest in cases with ≥4 PRLs (n = 30; β_add, 30.4; 95% CI, 15.6–45.2; p < 0.01). Subsequent multivariable analysis revealed that PRLs ≥2 cases also had higher MSSS (β_add, 1.1; 95% CI, 0.3–1.9; p < 0.01), whereas MSSS was not affected by DMT or T2 lesion load. On histopathology, both chronic active and smoldering lesions exhibited more severe acute axonal damage at the lesion edge than in the lesion center (edge vs center: p = 0.004 and p = 0.0002, respectively). Conclusion Chronic white matter inflammation was associated with increased levels of sNfL and disease severity in nonacute MS, suggesting that PRL contribute to clinically relevant, inflammation-driven neurodegeneration.

Progression independent of relapse activity (PIRA) is a crucial determinant of overall disability accumulation in multiple sclerosis (MS). Accelerated brain atrophy has been shown in patients experiencing PIRA. In this study, we assessed the relation between PIRA and neurodegenerative processes reflected by (1) longitudinal spinal cord atrophy and (2) brain paramagnetic rim lesions (PRLs). Besides, the same relationship was investigated in progressive MS (PMS). Last, we explored the value of cross-sectional brain and spinal cord volumetric measurements in predicting PIRA. From an ongoing multicentric cohort study, we selected patients with MS with (1) availability of a susceptibility-based MRI scan and (2) regular clinical and conventional MRI follow-up in the 4 years before the susceptibility-based MRI. Comparisons in spinal cord atrophy rates (explored with linear mixed-effect models) and PRL count (explored with negative binomial regression models) were performed between: (1) relapsing-remitting (RRMS) and PMS phenotypes and (2) patients experiencing PIRA and patients without confirmed disability accumulation (CDA) during follow-up (both considering the entire cohort and the subgroup of patients with RRMS). Associations between baseline MRI volumetric measurements and time to PIRA were explored with multivariable Cox regression analyses. In total, 445 patients with MS (64.9% female; mean [SD] age at baseline 45.0 [11.4] years; 11.2% with PMS) were enrolled. Compared with patients with RRMS, those with PMS had accelerated cervical cord atrophy (mean difference in annual percentage volume change [MD-APC] -1.41; p = 0.004) and higher PRL load (incidence rate ratio [IRR] 1.93; p = 0.005). Increased spinal cord atrophy (MD-APC -1.39; p = 0.0008) and PRL burden (IRR 1.95; p = 0.0008) were measured in patients with PIRA compared with patients without CDA; such differences were also confirmed when restricting the analysis to patients with RRMS. Baseline volumetric measurements of the cervical cord, whole brain, and cerebral cortex significantly predicted time to PIRA (all p ≤ 0.002). Our results show that PIRA is associated with both increased spinal cord atrophy and PRL burden, and this association is evident also in patients with RRMS. These findings further point to the need to develop targeted treatment strategies for PIRA to prevent irreversible neuroaxonal loss and optimize long-term outcomes of patients with MS.

Objective: To investigate the longitudinal dynamics of serum glial fibrillary acidic protein (sGFAP) and serum neurofilament light chain (sNfL) levels in people with multiple sclerosis (pwMS) under B‐cell depleting therapy (BCDT) and their capacity to prognosticate future progression independent of relapse activity (PIRA) events.Methods: A total of 362 pwMS (1,480 samples) starting BCDT in the Swiss Multiple Sclerosis (MS) Cohort were included. sGFAP levels in 2,861 control persons (4,943 samples) provided normative data to calculate adjusted Z scores.Results: Elevated sGFAP levels (Z score >1) at 1 year were associated with a higher hazard for PIRA (hazard ratio [HR]: 1.80 [95% CI: 1.17–2.78]; p = 0.0079) than elevated sNfL levels (HR, 1.45 [0.95–2.24], p = 0.0886) in a combined model. Independent of PIRA events, sGFAP levels longitudinally increased by 0.49 Z score units per 10 years follow‐up (estimate, 0.49 [0.29, 0.69], p < 0.0001). In patients experiencing PIRA, sGFAP Z scores were 0.52 Z score units higher versus stable patients (0.52 [0.22, 0.83], p = 0.0009). Different sNfL Z score trajectories were found in pwMS with versus without PIRA (interaction p = 0.0028), with an average decrease of 0.92 Z score units per 10 years observed without PIRA (−0.92 [−1.23, −0.60], p < 0.0001), whereas levels in patients with PIRA remained high.Interpretation: Elevated sGFAP and lack of drop in sNfL after BCDT start are associated with increased risk of future PIRA. These findings provide a rationale for combined monitoring of sNfL and sGFAP in pwMS starting BCDT to predict the risk of PIRA, and to use sGFAP as an outcome in clinical trials aiming to impact on MS progressive disease biology. ANN NEUROL 2025;97:104–115

Quantitative MRI (qMRI) probes the microstructural properties of the central nervous system (CNS) by providing biophysical measures of tissue characteristics. In this work, we aimed to (i) identify qMRI measures that distinguish histological lesion types in postmortem multiple sclerosis (MS) brains, especially the remyelinated ones; and to (ii) investigate the relationship between those measures and quantitative histological markers of myelin, axons, and astrocytes in the same experimental setting. Three fixed MS whole brains were imaged with qMRI at 3T to obtain magnetization transfer ratio (MTR), myelin water fraction (MWF), quantitative T1 (qT1), quantitative susceptibility mapping (QSM), fractional anisotropy (FA) and radial diffusivity (RD) maps. The identification of lesion types (active, inactive, chronic active, or remyelinated) and quantification of tissue components were performed using histological staining methods as well as immunohistochemistry and immunofluorescence. Pairwise logistic and LASSO regression models were used to identify the best qMRI discriminators of lesion types. The association between qMRI and quantitative histological measures was performed using Spearman's correlations and linear mixed‐effect models. We identified a total of 65 lesions. MTR and MWF best predicted the chance of a lesion to be remyelinated, whereas RD and QSM were useful in the discrimination of active lesions. The measurement of microstructural properties through qMRI did not show any difference between chronic active and inactive lesions. MWF and RD were associated with myelin content in both lesions and normal‐appearing white matter (NAWM), FA was the measure most associated with axon content in both locations, while MWF was associated with astrocyte immunoreactivity only in lesions. Moreover, we provided evidence of extensive astrogliosis in remyelinated lesions. Our study provides new information on the discriminative power of qMRI in differentiating MS lesions ‐especially remyelinated ones‐ as well as on the relative association between multiple qMRI measures and myelin, axon and astrocytes.

Myelin and iron play essential roles in remyelination processes of multiple sclerosis (MS) lesions. χ-separation, a novel biophysical model applied to multiecho T2*-data and T2-data, estimates the contribution of myelin and iron to the obtained susceptibility signal. We used this method to investigate myelin and iron levels in lesion and nonlesion brain areas in patients with MS and healthy individuals. This prospective MS cohort study included patients with MS fulfilling the McDonald Criteria 2017 and healthy individuals, aged 18 years or older, with no other neurologic comorbidities. Participants underwent MRI at baseline and after 2 years, including multiecho GRE-(T2*) and FAST-(T2) sequences. Using χ-separation, we generated myelin-sensitive and iron-sensitive susceptibility maps. White matter lesions (WMLs), cortical lesions (CLs), surrounding normal-appearing white matter (NAWM), and normal-appearing gray matter were segmented on fluid-attenuated inversion recovery and magnetization-prepared 2 rapid gradient echo images, respectively. Cross-sectional group comparisons used Wilcoxon rank-sum tests, longitudinal analyses applied Wilcoxon signed-rank tests. Associations with clinical outcomes (disease phenotype, age, sex, disease duration, disability measured by Expanded Disability Status Scale [EDSS], neurofilament light chain levels, and T2-lesion number and volume) were assessed using linear regression models. Of 168 patients with MS (median [interquartile range (IQR)] age 47.0 [21.7] years; 101 women; 6,898 WMLs, 775 CLs) and 103 healthy individuals (age 33.0 [10.5] years, 57 women), 108 and 62 were followed for a median of 2 years, respectively (IQR 0.1; 5,030 WMLs, 485 CLs). At baseline, WMLs had lower myelin (median 0.025 [IQR 0.015] parts per million [ppm]) and iron (0.017 [0.015] ppm) than the corresponding NAWM (myelin 0.030 [0.012]; iron 0.019 [0.011] ppm; both p < 0.001). After 2 years, both myelin (0.027 [0.014] ppm) and iron had increased (0.018 [0.015] ppm; both p < 0.001). Younger age (p < 0.001, b = −5.111 × 10⁻⁵), lower disability (p = 0.04, b = −2.352 × 10⁻⁵), and relapsing-remitting phenotype (RRMS, 0.003 [0.01] vs primary progressive 0.002 [IQR 0.01], p < 0.001; vs secondary progressive 0.0004 [IQR 0.01], p < 0.001) at baseline were associated with remyelination. Increment of myelin correlated with clinical improvement measured by EDSS (p = 0.015, b = −6.686 × 10⁻⁴). χ-separation, a novel mathematical model applied to multiecho T2*-images and T2-images shows that young RRMS patients with low disability exhibit higher remyelination capacity, which correlated with clinical disability over a 2-year follow-up.

In multiple sclerosis (MS) patients under therapy, the increase of serum glial fibrillary acidic protein (sGFAP) concentrations is associated with the course of ‘progression in absence of relapse’ (PIRA). While serum neurofilament light chain (sNfL) reflects both response as well as insufficient or lack of efficiency of disease-modifying therapies (DMT), the longitudinal course of sGFAP levels as a drug response marker for future PIRA in relation to specific types of DMT is less clear. We aimed to compare the predictive capacity of sGFAP and sNfL for PIRA and relapse activity and the longitudinal course in people with MS (PwMS) treated with fingolimod, based on Z scores derived from normative values. Overall, 420 PwMS under fingolimod treatment with follow-up of 9.1 years (interquartile range: 7.0–11.0) from the Swiss MS Cohort, contributing 2935 longitudinal serum samples, were included. A reference data set for sGFAP established from 4297 healthy controls across three European and North American cohorts was used to calculate Z scores. The longitudinal course and the predictive capacity of biomarkers for time to PIRA and relapse were assessed by Cox proportional hazards and linear mixed-effects models. In controls, sGFAP concentrations were 13.6% higher in females than males and increased exponentially with age. Altogether, 31.0% of PwMS experienced ≥1 PIRA event. Elevated sGFAP Z scores (>0.75) were associated with increased risk of PIRA [hazard ratio (HR): 1.64; 95% confidence interval (CI): 1.16–2.32; P = 0.006], while this was not the case for sNfL. Conversely, elevated sNfL predicted relapses (HR: 1.58; 95% CI: 1.13–2.23; P = 0.008), while sGFAP did not. Both biomarkers decreased under treatment: sGFAP by 0.19 Z score units (ZSU)/10 years (95% CI: −0.27 to −0.11; P < 0.001) and sNfL by 0.16 ZSU/10 years (95% CI: −0.27 to −0.06; P = 0.002). Serum GFAP remained elevated in PwMS with future PIRA events (estimate: 0.29; 95% CI: 0.07–0.50; P = 0.009); no such association was found for sNfL. Serum GFAP and sNfL Z scores provide complementary predictive capacity for PIRA and relapse risk. The decrease of sGFAP under fingolimod is a feature not observed with other types of DMT and may hint to a specific anti-neurodegenerative effect of Sphingosine-1-phosphate-receptor modulators on astrocytes.