Pooled analysis of multiple sclerosis findings on multisite 7 Tesla MRI: Protocol and initial observations.

Although 7 T MRI research has contributed much to our understanding of multiple sclerosis (MS) pathology, most prior data has come from small, single-center studies with varying methods. In order to truly know if such findings have widespread applicability, multicenter methods and studies are needed. To address this, members of the North American Imaging in MS (NAIMS) Cooperative worked together to create a multicenter collaborative study of 7 T MRI in MS. In this manuscript, we describe the methods we have developed for the purpose of pooling together a large, retrospective dataset of 7 T MRIs acquired in multiple MS studies at five institutions. To date, this group has contributed five-hundred and twenty-eight 7 T MRI scans from 350 individuals with MS to a common data repository, with plans to continue to increase this sample size in the coming years. We have developed unified methods for image processing for data harmonization and lesion identification/segmentation. We report here our initial observations on intersite differences in acquisition, which includes site/device differences in brain coverage and image quality. We also report on the development of our methods and training of image evaluators, which resulted in median Dice Similarity Coefficients for trained raters' annotation of cortical and deep gray matter lesions, paramagnetic rim lesions, and meningeal enhancement between 0.73 and 0.82 compared to final consensus masks. We expect this publication to act as a resource for other investigators aiming to combine multicenter 7 T MRI datasets for the study of MS, in addition to providing a methodological reference for all future analysis projects to stem from the development of this dataset.

PARE: A framework for removal of confounding effects from any distance-based dimension reduction method.

Dimension reduction tools preserving similarity and graph structure such as t-SNE and UMAP can capture complex biological patterns in high-dimensional data. However, these tools typically are not designed to separate effects of interest from unwanted effects due to confounders. We introduce the partial embedding (PARE) framework, which enables removal of confounders from any distance-based dimension reduction method. We then develop partial t-SNE and partial UMAP and apply these methods to genomic and neuroimaging data. For lower-dimensional visualization, our results show that the PARE framework can remove batch effects in single-cell sequencing data as well as separate clinical and technical variability in neuroimaging measures. We demonstrate that the PARE framework extends dimension reduction methods to highlight biological patterns of interest while effectively removing confounding effects.

Glial Activity Load on PET Reveals Persistent "Smoldering" Inflammation in MS Despite Disease-Modifying Treatment: 18 F-PBR06 Study.

PURPOSE OF THE REPORT: 18 F-PBR06-PET targeting 18-kDa translocator protein can detect abnormal microglial activation (MA) in multiple sclerosis (MS). The objectives of this study are to develop individualized mapping of MA using 18 F-PBR06, to determine the effect of disease-modifying treatment (DMT) efficacy on reducing MA, and to determine its clinical, radiological, and serological correlates in MS patients. PATIENTS AND METHODS: Thirty 18 F-PBR06-PET scans were performed in 22 MS patients (mean age, 46 ± 13 years; 16 females) and 8 healthy controls (HCs). Logarithmically transformed "glial activity load on PET" scores (calculated as the sum of voxel-by-voxel z -scores ≥4), "lnGALP," were compared between MS and HC and between MS subjects on high-efficacy DMTs (H-DMT, n = 13) and those on no or lower-efficacy treatment, and correlated with clinical measures, serum biomarkers, and cortical thickness. RESULTS: Cortical gray matter (CoGM) and white matter (WM) lnGALP scores were higher in MS versus HC (+33% and +48%, P < 0.001). In H-DMT group, CoGM and WM lnGALP scores were significantly lower than lower-efficacy treatment ( P < 0.01) but remained abnormally higher than in HC group ( P = 0.006). Within H-DMT patients, CoGM lnGALP scores correlated positively with physical disability, fatigue and serum glial fibrillary acid protein levels ( r = 0.65-0.79, all P 's < 0.05), and inversely with cortical thickness ( r = -0.66, P < 0.05). CONCLUSIONS: High-efficacy DMTs decrease, but do not normalize, CoGM and WM MA in MS patients. Such "residual" MA in CoGM is associated with clinical disability, serum biomarkers, and cortical degeneration. Individualized mapping of translocator protein PET using 18 F-PBR06 is clinically feasible and can potentially serve as an imaging biomarker for evaluating "smoldering" inflammation in MS patients.

Increasing Neurofilament and Glial Fibrillary Acidic Protein After Treatment Discontinuation Predicts Multiple Sclerosis Disease Activity.

BACKGROUND AND OBJECTIVES: Stable patients with multiple sclerosis (MS) may discontinue treatment, but the risk of disease activity is unknown. Serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP) are biomarkers of subclinical disease activity and may help risk stratification. In this study, sNfL and sGFAP levels in stable patients were evaluated before and after treatment discontinuation to determine association with disease activity. METHODS: This observational study included patients enrolled in the Comprehensive Longitudinal Investigation in MS at the Brigham and Women's Hospital who discontinued treatment after >2 years disease activity-free. Two serum samples within 2 years, before and after treatment stop, were sent for sNfL and sGFAP measurements by single-molecule array. Biannual neurologic examinations and yearly MRI scans determined disease activity by 3 time-to-event outcomes: 6-month confirmed disability worsening (CDW), clinical attacks, and MRI activity (new T2 or contrast-enhancing lesions). Associations between each outcome and log-transformed sNfL and sGFAP levels pretreatment stop and posttreatment stop and the percent change were estimated using multivariable Cox regression analysis adjusting for age, disability, disease duration, and duration from attack before treatment stop. RESULTS: Seventy-eight patients (92% female) discontinued treatment at a median (interquartile range) age of 48.5 years (39.0-55.7) and disease duration of 12.3 years (7.5-18.8) and were followed up for 6.3 years (4.2-8.5). CDW occurred in 27 patients (35%), new attacks in 19 (24%), and new MRI activity in 26 (33%). Higher posttreatment stop sNfL level was associated with CDW (adjusted hazard ratio (aHR) 2.80, 95% CI 1.36-5.76, p = 0.005) and new MRI activity (aHR 3.09, 95% CI 1.42-6.70, p = 0.004). Patients who had >100% increase in sNfL level from pretreatment stop to posttreatment stop had greater risk of CDW (HR 3.87, 95% CI 1.4-10.7, p = 0.009) and developing new MRI activity (HR 4.02, 95% CI 1.51-10.7, p = 0.005). Patients who had >50% increase in sGFAP level also had greater risk of CDW (HR 5.34, 95% CI 1.4-19.9, p = 0.012) and developing new MRI activity (HR 5.16, 95% CI 1.71-15.6, p = 0.004). DISCUSSION: Stable patients who discontinue treatment may be risk stratified by sNfL and sGFAP levels measured before and after discontinuing treatment. Further studies are needed to validate findings and determine whether resuming treatment in patients with increasing biomarker levels reduces risk of subsequent disease activity.

Accuracy of serum neurofilament light to identify contrast-enhancing lesions in multiple sclerosis.

BACKGROUND: Contrast-enhancing magnetic resonance imaging (MRI) lesions (CELs) indicate acute multiple sclerosis inflammation. Serum biomarkers, neurofilament light (sNfL), and glial fibrillary acidic protein (sGFAP) may increase in the presence of CELs, and indicate a need to perform MRI. OBJECTIVE: We assessed the accuracy of biomarkers to detect CELs. METHODS: Patients with two gadolinium-enhanced MRIs and serum biomarkers tested within 3 months were included (N = 557, 66% female). Optimal cut-points from Bland-Altman analysis for spot biomarker level and Youden's index for delta-change from remission were evaluated. RESULTS: A total of 116 patients (21%) had CELs. A spot sNfL measurement >23.0 pg/mL corresponded to 7.0 times higher odds of CEL presence (95% CI: 3.8, 12.8), with 25.9% sensitivity, 95.2% specificity, operating characteristic curve (AUC) 0.61; while sNfL delta-change >30.8% from remission corresponded to 5.0 times higher odds (95% CI: 3.2, 7.8), 52.6% sensitivity, 81.9% specificity, AUC 0.67. sGFAP had poor CEL detection. In patients > 50 years, neither cut-point remained significant. sNfL delta-change outperformed spot levels at identifying asymptomatic CELs (AUC 0.67 vs 0.59) and in patients without treatment escalation between samples (AUC 0.67 vs 0.57). CONCLUSION: Spot sNfL >23.0 pg/mL or a 30.8% increase from remission provides modest prediction of CELs in patients <50 years; however, low sNfL does not obviate the need for MRI.

Intersite brain MRI volumetric biases persist even in a harmonized multisubject study of multiple sclerosis.

BACKGROUND AND PURPOSE: Multicenter study designs involving a variety of MRI scanners have become increasingly common. However, these present the issue of biases in image-based measures due to scanner or site differences. To assess these biases, we imaged 11 volunteers with multiple sclerosis (MS) with scan and rescan data at four sites. METHODS: Images were acquired on Siemens or Philips scanners at 3 Tesla. Automated white matter lesion detection and whole-brain, gray and white matter, and thalamic volumetry were performed, as well as expert manual delineations of T1 magnetization-prepared rapid acquisition gradient echo and T2 fluid-attenuated inversion recovery lesions. Random-effect and permutation-based nonparametric modeling was performed to assess differences in estimated volumes within and across sites. RESULTS: Random-effect modeling demonstrated model assumption violations for most comparisons of interest. Nonparametric modeling indicated that site explained >50% of the variation for most estimated volumes. This expanded to >75% when data from both Siemens and Philips scanners were included. Permutation tests revealed significant differences between average inter- and intrasite differences in most estimated brain volumes (P < .05). The automatic activation of spine coil elements during some acquisitions resulted in a shading artifact in these images. Permutation tests revealed significant differences between thalamic volume measurements from acquisitions with and without this artifact. CONCLUSION: Differences in brain volumetry persisted across MR scanners despite protocol harmonization. These differences were not well explained by variance component modeling; however, statistical innovations for mitigating intersite differences show promise in reducing biases in multicenter studies of MS.

Multiple sclerosis lesions that impair memory map to a connected memory circuit.

BACKGROUND: Nearly 1 million Americans are living with multiple sclerosis (MS) and 30-50% will experience memory dysfunction. It remains unclear whether this memory dysfunction is due to overall white matter lesion burden or damage to specific neuroanatomical structures. Here we test if MS memory dysfunction is associated with white matter lesions to a specific brain circuit. METHODS: We performed a cross-sectional analysis of standard structural images and verbal memory scores as assessed by immediate recall trials from 431 patients with MS (mean age 49.2 years, 71.9% female) enrolled at a large, academic referral center. White matter lesion locations from each patient were mapped using a validated algorithm. First, we tested for associations between memory dysfunction and total MS lesion volume. Second, we tested for associations between memory dysfunction and lesion intersection with an a priori memory circuit derived from stroke lesions. Third, we performed mediation analyses to determine which variable was most associated with memory dysfunction. Finally, we performed a data-driven analysis to derive de-novo brain circuits for MS memory dysfunction using both functional (n = 1000) and structural (n = 178) connectomes. RESULTS: Both total lesion volume (r = 0.31, p < 0.001) and lesion damage to our a priori memory circuit (r = 0.34, p < 0.001) were associated with memory dysfunction. However, lesion damage to the memory circuit fully mediated the association of lesion volume with memory performance. Our data-driven analysis identified multiple connections associated with memory dysfunction, including peaks in the hippocampus (T = 6.05, family-wise error p = 0.000008), parahippocampus, fornix and cingulate. Finally, the overall topography of our data-driven MS memory circuit matched our a priori stroke-derived memory circuit. CONCLUSIONS: Lesion locations associated with memory dysfunction in MS map onto a specific brain circuit centered on the hippocampus. Lesion damage to this circuit fully mediated associations between lesion volume and memory. A circuit-based approach to mapping MS symptoms based on lesions visible on standard structural imaging may prove useful for localization and prognosis of higher order deficits in MS.

Familial Mediterranean Fever and multiple sclerosis treated with ocrelizumab: Case report.

BACKGROUND: Familial Mediterranean Fever (FMF) is associated with increased risk of multiple sclerosis (MS). Optimal treatment of patients with comorbid FMF and MS remains uncertain. CASE: A 28-year-old woman with FMF, treated with colchicine, had symptomatic onset of relapsing remitting MS following four simultaneous vaccines. MRI brain with a 7-Tesla magnet demonstrated several areas of leptomeningeal enhancement with predominant linear, spread/fill and rare nodular patterns. Central vein signs were present in supratentorial white matter lesions. She received four cycles of ocrelizumab and achieved no evidence of disease activity (NEDA-3) at 20 months' follow up. DISCUSSION: FMF with incident CNS demyelinating disease demonstrated neuroimaging features typical for classic RRMS including the central vein sign and leptomeningeal enhancement. Treatment with B-cell depleting therapy for FMF-MS led to clinical stability and symptomatic improvement at 20 months' follow up. We add to the sparse literature characterizing the course of FMF as a genetic risk factor for CNS demyelinating disease, demonstrating pathognomonic imaging features of MS on 7 T imaging and treatment efficacy with B-cell depletion.

Preserved T cell but attenuated antibody response in MS patients on fingolimod and ocrelizumab following 2nd and 3rd SARS-CoV-2 mRNA vaccine.

Background: There is limited knowledge about T cell responses in patients with multiple sclerosis (MS) after 3 doses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccine. Objectives: Assess the SARS-CoV-2 spike antibody and T cell responses in MS patients and healthy controls (HCs) after 2 doses (2-vax) and 3 doses (3-vax) of SARS-CoV-2 mRNA vaccination. Methods: We studied seroconversion rates and T cell responses by flow cytometry in HC and MS patients on fingolimod or ocrelizumab. Results: After 2-vax, 8/33 (24.2%) patients in ocrelizumab group, 5/7 (71.4%) in fingolimod group, and 29/29 (100%) in HC group (P = 5.7 × 10-11) seroconverted. After 3-vax, 9/22 (40.9%) patients in ocrelizumab group, 19/21 (90.5%) in fingolimod group, and 7/7 (100%) in HC group seroconverted (P = 0.0003). The percentage of SARS-CoV-2 peptide reactive total CD4+ T cells increased in HC and ocrelizumab group but not in fingolimod group after 2-vax and 3-vax (P < 0.0001). The percentage of IFNγ and TNFα producing total CD4+ and CD8+ T cells increased in fingolimod group as compared to HC and ocrelizumab group after 2-vax and 3-vax (P < 0.0001). Conclusions: MS patients on ocrelizumab and fingolimod had attenuated humoral responses, but preserved cytokine producing T cell responses compared to HCs after SARS-CoV-2 mRNA vaccination. Clinical Trials Registration: NCT05060354.

Early neurofilament light and glial fibrillary acidic protein levels improve predictive models of multiple sclerosis outcomes.

BACKGROUND: Early risk-stratification in multiple sclerosis (MS) may impact treatment decisions. Current predictive models have identified that clinical and imaging characteristics of aggressive disease are associated with worse long-term outcomes. Serum biomarkers, neurofilament (sNfL) and glial fibrillary acidic protein (sGFAP), reflect subclinical disease activity through separate pathological processes and may contribute to predictive models of clinical and MRI outcomes. METHODS: We conducted a retrospective analysis of the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB study), where patients with multiple sclerosis are seen every 6 months and undergo Expanded Disability Status Scale (EDSS) assessment, have annual brain MRI scans where volumetric analysis is conducted to calculate T2-lesion volume (T2LV) and brain parenchymal fraction (BPF), and donate a yearly blood sample for subsequent analysis. We included patients with newly diagnosed relapsing-remitting MS and serum samples obtained at baseline visit and 1-year follow-up (both within 3 years of onset), and were assessed at 10-year follow-up. We measured sNfL and sGFAP by single molecule array at baseline visit and at 1-year follow-up. A predictive clinical model was developed using age, sex, Expanded Disability Status Scale (EDSS), pyramidal signs, relapse rate, and spinal cord lesions at first visit. The main outcome was odds of developing of secondary progressive (SP)MS at year 10. Secondary outcomes included 10-year EDSS, brain T2LV and BPF. We compared the goodness-of-fit of the predictive clinical model with and without sNfL and sGFAP at baseline and 1-year follow-up, for each outcome by area under the receiver operating characteristic curve (AUC) or R-squared. RESULTS: A total 144 patients with median MS onset at age 37.4 years (interquartile range: 29.4-45.4), 64% female, were included. SPMS developed in 25 (17.4%) patients. The AUC for the predictive clinical model without biomarker data was 0.73, which improved to 0.77 when both sNfL and sGFAP were included in the model (P = 0.021). In this model, higher baseline sGFAP associated with developing SPMS (OR=3.3 [95%CI:1.1,10.6], P = 0.04). Adding 1-year follow-up biomarker levels further improved the model fit (AUC = 0.79) but this change was not statistically significant (P = 0.15). Adding baseline biomarker data also improved the R-squared of clinical models for 10-year EDSS from 0.24 to 0.28 (P = 0.032), while additional 1-year follow-up levels did not. Baseline sGFAP was associated with 10-year EDSS (ß=0.58 [95%CI:0.00,1.16], P = 0.05). For MRI outcomes, baseline biomarker levels improved R-squared for T2LV from 0.12 to 0.27 (P<0.001), and BPF from 0.15 to 0.20 (P = 0.042). Adding 1-year follow-up biomarker data further improved T2LV to 0.33 (P = 0.0065) and BPF to 0.23 (P = 0.048). Baseline sNfL was associated with T2LV (ß=0.34 [95%CI:0.21,0.48], P<0.001) and 1-year follow-up sNfL with BPF (ß=-2.53% [95%CI:-4.18,-0.89], P = 0.003). CONCLUSIONS: Early biomarker levels modestly improve predictive models containing clinical and MRI variables. Worse clinical outcomes, SPMS and EDSS, are associated with higher sGFAP levels and worse MRI outcomes, T2LV and BPF, are associated with higher sNfL levels. Prospective study implementing these predictive models into clinical practice are needed to determine if early biomarker levels meaningfully impact clinical practice.

Deconfounded Dimension Reduction via Partial Embeddings.

Dimension reduction tools preserving similarity and graph structure such as t-SNE and UMAP can capture complex biological patterns in high-dimensional data. However, these tools typically are not designed to separate effects of interest from unwanted effects due to confounders. We introduce the partial embedding (PARE) framework, which enables removal of confounders from any distance-based dimension reduction method. We then develop partial t-SNE and partial UMAP and apply these methods to genomic and neuroimaging data. Our results show that the PARE framework can remove batch effects in single-cell sequencing data as well as separate clinical and technical variability in neuroimaging measures. We demonstrate that the PARE framework extends dimension reduction methods to highlight biological patterns of interest while effectively removing confounding effects.

Serum NfL but not GFAP predicts cognitive decline in active progressive multiple sclerosis patients.

BACKGROUND: Cognitive decline is inadequately captured by the standard neurological examination. Serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) are biomarkers of neuronal damage and astrocytic reactivity that may offer an accessible measure of the multiple sclerosis (MS) pathology linked to cognitive decline. OBJECTIVE: To investigate the association of sNfL and sGFAP with cognitive decline in MS patients at high risk for progressive pathology. METHODS: We included 94 MS patients with sustained Expanded Disability Status Score (EDSS) ⩾ 3, available serum samples and cognitive assessment performed by symbol digit modalities test (SDMT) over a median of 3.1 years. The visit for sGFAP/sNfL quantification was at confirmed EDSS ⩾ 3. Linear regression analysis on log-transformed sGFAP/sNfL assessed the association with current and future SDMT. Analyses were adjusted for age, sex, EDSS, treatment group, and recent relapse. RESULTS: sNfL was significantly associated with concurrent SDMT (adjusted change in mean SDMT = -4.5; 95% confidence interval (CI): -8.7, -0.2; p = 0.039) and predicted decline in SDMT (adjusted change in slope: -1.14; 95% CI: -1.83, -0.44; p = 0.001), particularly in active patients. sGFAP was not associated with concurrent or future SDMT. CONCLUSIONS: Higher levels of sNfL were associated with cognitive impairment and predicted cognitive decline in MS patients at high risk for having an underlying progressive pathology.

Exploring the effect of glatiramer acetate on cerebral gray matter atrophy in multiple sclerosis.

BACKGROUND AND PURPOSE: Cerebral gray matter (GM) atrophy is a proposed measure of neuroprotection in multiple sclerosis (MS). Glatiramer acetate (GA) limits clinical relapses, MRI lesions, and whole brain atrophy in relapsing-remitting MS (RRMS). The effect of GA on GM atrophy remains unclear. We assessed GM atrophy in patients with RRMS starting GA therapy in comparison to a cohort of patients with clinically benign RRMS (BMS). DESIGN/METHODS: We studied 14 patients at GA start [age (mean ± SD) 44.2 ± 7.0 years, disease duration (DD) 7.2 ± 6.4 years, Expanded Disability Status Scale score (EDSS) (median,IQR) 1.0,2.0] and 6 patients with BMS [age 43.0 ± 6.1 years, DD 18.1 ± 8.4 years, EDSS 0.5,1.0]. Brain MRI was obtained at baseline and one year later (both groups) and two years later in all patients in the GA group except one who was lost to follow-up. Semi-automated algorithms assessed cerebral T2 hyperintense lesion volume (T2LV), white matter fraction (WMF), GM fraction (GMF), and brain parenchymal fraction (BPF). The exact Wilcoxon-Mann-Whitney test compared the groups. The Wilcoxon signed rank test assessed longitudinal changes within groups. RESULTS: During the first year, MRI changes did not differ significantly between groups (p > 0.15). Within the BMS group, WMF and BPF decreased during the first year (p = 0.03). Within the GA group, there was no significant change in MRI measures during each annual period (p > 0.05). Over two years, the GA group had a significant increase in T2LV and decrease in WMF (p < 0.05), while GMF and BPF remained stable (p > 0.05). MRI changes in brain volumes (GMF or WMF) in the first year in the GA group were not significantly different from those in the BMS group (p > 0.5). CONCLUSIONS: In this pilot study with a small sample size, patients with RRMS started on GA did not show significant GM or whole brain atrophy over 2 years, resembling MS patients with a clinically benign disease course.

Serum GFAP and NfL Levels Differentiate Subsequent Progression and Disease Activity in Patients With Progressive Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Neurodegeneration and astrocytic activation are pathologic hallmarks of progressive multiple sclerosis (MS) and can be quantified by serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP). We investigated sNfL and sGFAP as tools for stratifying patients with progressive MS based on progression and disease activity status. METHODS: We leveraged our Comprehensive Longitudinal Investigation of MS at the Brigham and Women's Hospital (CLIMB) natural history study, which includes clinical, MRI data and serum samples collected over more than 20 years. We included patients with MS with a confirmed Expanded Disability Status Scale (EDSS) score ≥3 that corresponds with our classifier for patients at high risk of underlying progressive pathology. We analyzed sNfL and sGFAP within 6 months from the confirmed EDSS score ≥3 corresponding with our baseline visit. Patients who further developed 6-month confirmed disability progression (6mCDP) were classified as progressors. We further stratified our patients into active/nonactive based on new brain/spinal cord lesions or relapses in the 2 years before baseline or during follow-up. Statistical analysis on log-transformed sGFAP/sNfL assessed the baseline association with demographic, clinical, and MRI features and associations with future disability. RESULTS: We included 257 patients with MS who had an average EDSS score of 4.0 and a median follow-up after baseline of 7.6 years. sNfL was higher in patients with disease activity in the 2 years before baseline (adjusted ß = 1.21; 95% CI 1.04-1.42; p = 0.016), during the first 2 years of follow-up (adjusted ß = 1.17; 95% CI = 1.01-1.36; p = 0.042). sGFAP was not increased in the presence of disease activity. Higher sGFAP levels, but not sNfL levels, were associated with higher risk of 6mCDP (adjusted hazard ratio [HR] = 1.71; 95% CI = 1.19-2.45; p = 0.004). The association was stronger in patients with low sNfL (adjusted HR = 2.44; 95% CI 1.32-4.52; p = 0.005) and patients who were nonactive in the 2 years prior or after the sample. DISCUSSION: Higher levels of sGFAP correlated with subsequent progression, particularly in nonactive patients, whereas sNfL reflected acute disease activity in patients with MS at high risk of underlying progressive pathology. Thus, sGFAP and sNfL levels may be used to stratify patients with progressive MS for clinical research studies and clinical trials and may inform clinical care.

Younger age at multiple sclerosis onset is associated with worse outcomes at age 50.

OBJECTIVE: Older age at multiple sclerosis (MS) onset has been associated with worse 10-year outcomes. However, disease duration often exceeds 10 years and age-related comorbidities may also contribute to disability. We investigated patients with>10 years disease duration to determine how age at MS onset is associated with clinical, MRI and occupational outcomes at age 50. METHODS: We included patients enrolled in the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital with disease duration>10 years. Outcomes at age 50 included the Expanded Disability Status Scale (EDSS), development of secondary-progressive multiple sclerosis (SPMS), brain T2-lesion volume (T2LV) and brain parenchymal fraction (BPF), and occupational status. We assessed how onset age was independently associated with each outcome when adjusting for the date of visit closest to age 50, sex, time to first treatment, number of treatments by age 50 and exposure to high-efficacy treatments by age 50. RESULTS: We included 661 patients with median onset at 31.4 years. The outcomes at age 50 were worse the younger first symptoms developed: for every 5 years earlier, the EDSS was 0.22 points worse (95% CI: 0.04 to 0.40; p=0.015), odds of SPMS 1.33 times higher (95% CI: 1.08 to 1.64; p=0.008), T2LV 1.86 mL higher (95% CI: 1.02 to 2.70; p<0.001), BPF 0.97% worse (95% CI: 0.52 to 1.42; p<0.001) and odds of unemployment from MS 1.24 times higher (95% CI: 1.01 to 1.53; p=0.037). CONCLUSIONS: All outcomes at age 50 were worse in patients with younger age at onset. Decisions to provide high-efficacy treatments should consider younger age at onset, equating to a longer expected disease duration, as a poor prognostic factor.

Humoral response to COVID-19 vaccination in MS patients on disease modifying therapy: Immune profiles and clinical outcomes.

BACKGROUND: Patients with multiple sclerosis (MS) on some disease modifying therapies (DMTs), particularly anti-CD20 and sphingosine-1-phosphate (S1P) modulators, are at increased risk of severe Coronavirus Disease 19 (COVID-19) and death. COVID-19 vaccinations are effective in preventing infection and severe disease, but humoral response to vaccination and outcomes of COVID-19 infection after vaccination in MS patients on DMTs remain less understood. METHODS: In this retrospective single-center study, patients enrolled in the CLIMB (Comprehensive Longitudinal Investigation of Multiple Sclerosis at Brigham and Women's Hospital) study and biorepository who had been vaccinated against COVID-19 and had SARS-CoV-2 spike antibody (anti-SARS-CoV-2 S Roche-Elecsys) testing were identified and compared to healthy controls. Demographic data, serum immune profiles including lymphocyte count, B-cell count, and immunoglobulins, and clinical outcome of COVID-19 infection were collected. RESULTS: 254 patients (73.2% female, mean (SD) age 52.9 (11.2) years) were identified. When controlling for age, time since vaccination, and vaccine type, patients on fingolimod, ocrelizumab, rituximab, mycophenolate mofetil, natalizumab and teriflunomide had significantly lower levels of spike antibodies compared to healthy controls (n = 34). Longer duration of treatment was associated with lower spike antibody levels in patients on anti-CD20 therapy (p = 0.016) and S1P modulators (p = 0.016) compared to healthy controls. In patients on anti-CD20 therapy, higher spike antibody levels were associated with higher CD20 cell count (p<0.001), and longer time since last anti-CD20 therapy infusion (p<0.001). 92.8% (13/14) vaccine responders (spike antibody titer >100 ug/dL) on anti-CD20 therapy demonstrated B-cell reconstitution (mean CD20 3.6%). Only 1 out of 86 patients with CD20 of 0% had a measurable spike antibody response to vaccination. During follow-up (mean 270 days), five patients were diagnosed with COVID-19 after vaccination (incidence 1.9%), all of whom had spike antibody < 20 ug/dL. No patients required ICU care or died. CONCLUSIONS: Patients on some DMTs demonstrate reduced humoral immunity after Sars-CoV-2 vaccination. Longer duration of anti-CD20 therapy and reduced CD20 cell count is associated with blunted humoral response to vaccination. CD20 reconstitution >0.1% appears necessary, but not always sufficient, for humoral response to vaccination. Breakthrough COVID-19 infection in our cohort of MS patients on DMT was higher than in population studies. We propose that adjustment of B-cell therapy administration to allow for B-cell reconstitution prior to vaccination should be considered.

Multisite MRI reproducibility of lateral ventricular volume using the NAIMS cooperative pilot dataset.

BACKGROUND AND PURPOSE: The North American Imaging in Multiple Sclerosis (NAIMS) multisite project identified interscanner reproducibility issues with T1-based whole brain volume (WBV). Lateral ventricular volume (LVV) acquired on T2-fluid-attenuated inverse recovery (FLAIR) scans has been proposed as a robust proxy measure. Therefore, we sought to determine the relative magnitude of scanner-induced T2-FLAIR-based LVV and T1-based WBV measurement errors in relation to clinically meaningful changes. METHODS: This was a post hoc analysis of the NAIMS pilot dataset in which a relapsing-remitting MS patient with no intrastudy clinical or radiological activity was imaged twice on seven different Siemens scanners across the United States. LVV was determined using the automated NeuroSTREAM technique on T2-FLAIR and WBV was determined with SIENAX on high-resolution T1-MPRAGE. Average LVV and WBV were measured, and absolute intrascanner and interscanner coefficients of variation (CoVs) were calculated. The variabilities were compared to previously established annual pathological and clinically meaningful cutoffs of 0.40% for WBV and of 3.51% for LVV. RESULTS: Mean LVV across all seven scan/rescan pairs was 45.87 ± 1.15 ml. Average LVV intrascanner CoV was 1.42% and interscanner CoV was 1.78%, both smaller than the reported annualized clinically meaningful cutoff of 3.51%. In contrast, intra- and interscanner CoVs for WBV (0.99% and 1.15%) were both higher than the established cutoff of 0.40%. Individually, 1/7 intrasite and 2/7 intersite pair-wise LVV comparisons were above the 3.51% cutoff, whereas 4/7 intrasite and 7/7 intersite WBV comparisons were above the 0.40% cutoff. CONCLUSION: Fully automated LVV segmentation has higher absolute variability than WBV, but much lower relative variability compared to clinically relevant changes, and may therefore be a meaningful proxy outcome measure of neurodegeneration.

Anti-SARS-CoV-2 monoclonal antibodies for the treatment of active COVID-19 in multiple sclerosis: An observational study.

Monoclonal antibodies (mAbs) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) received emergency use authorization for the acute treatment of COVID-19. We are not aware of published data on their use in immunosuppressed people with multiple sclerosis (pwMS). We report 23 pwMS (mean age = 49 years, ocrelizumab (n = 19), fingolimod (n = 2), vaccinated with at least an initial series (n = 19)) who received mAb for acute COVID-19. Following mAb receipt, approximately half recovered in <7 days (48%). There were no adverse events or deaths. Use of mAb for pwMS treated with fingolimod or ocrelizumab was not observed to be harmful and is likely helpful for treatment of acute COVID-19.

Early Predictors of Clinical and MRI Outcomes Using Least Absolute Shrinkage and Selection Operator (LASSO) in Multiple Sclerosis.

OBJECTIVE: The objective of this study was to identify predictors in common between different clinical and magnetic resonance imaging (MRI) outcomes in multiple sclerosis (MS) by comparing predictive models. METHODS: We analyzed 704 patients from our center seen at MS onset, measuring 37 baseline demographic, clinical, treatment, and MRI predictors, and 10-year outcomes. Our primary aim was identifying predictors in common among clinical outcomes: aggressive MS, benign MS, and secondary-progressive (SP)MS. We also investigated MRI outcomes: T2 lesion volume (T2LV) and brain parenchymal fraction (BPF). The performance of the full 37-predictor model was compared with a least absolute shrinkage and selection operator (LASSO)-selected model of predictors in common between each outcome by the area under the receiver operating characteristic curves (AUCs). RESULTS: The full 37-predictor model was highly predictive of clinical outcomes: in-sample AUC was 0.91 for aggressive MS, 0.81 for benign MS, and 0.81 for SPMS. After variable selection, 10 LASSO-selected predictors were in common between each clinical outcome: age, Expanded Disability Status Scale, pyramidal, cerebellar, sensory and bowel/bladder signs, timed 25-foot walk ≥6 seconds, poor attack recovery, no sensory attacks, and time-to-treatment. This reduced model had comparable cross-validation AUC as the full 37-predictor model: 0.84 versus 0.81 for aggressive MS, 0.75 versus 0.73 for benign MS, and 0.76 versus 0.75 for SPMS, respectively. In contrast, 10-year MRI outcomes were more strongly influenced by initial T2LV and BPF than clinical outcomes. INTERPRETATION: Early prognostication of MS is possible using LASSO modeling to identify a limited set of accessible clinical features. These predictive models can be clinically usable in treatment decision making once implemented into web-based calculators. ANN NEUROL 2022;92:87-96.

Serum NfL levels in the first five years predict 10-year thalamic fraction in patients with MS.

BACKGROUND: Serum neurofilament light chain (sNfL) levels are associated with relapses, MRI lesions, and brain volume in multiple sclerosis (MS). OBJECTIVE: To explore the value of early serum neurofilament light (sNfL) measures in prognosticating 10-year regional brain volumes in MS. METHODS: Patients with MS enrolled in the Comprehensive Longitudinal Investigations in MS at Brigham and Women's Hospital (CLIMB) study within five years of disease onset who had annual blood samples from years 1-10 (n = 91) were studied. sNfL was measured with a single molecule array (SIMOA) assay. We quantified global cortical thickness and normalized deep gray matter (DGM) volumes (fractions of the thalamus, caudate, putamen, and globus pallidus) from high-resolution 3 T MRI at 10 years. Correlations between yearly sNfL levels and 10-year MRI outcomes were assessed using linear regression models. RESULTS: sNfL levels from years 1 and 2 were associated with 10-year thalamus fraction. Early sNfL levels were not associated with 10-year putamen, globus pallidus or caudate fractions. At 10 years, cortical thickness was not associated with early sNfL levels, but was weakly correlated with total DGM fraction. CONCLUSIONS: Early sNfL levels correlate with 10-year thalamic volume, supporting its role as a prognostic biomarker in MS.