The role of CD56bright NK cells in neurodegenerative disorders.

Emerging evidence suggests a potential role for natural killer (NK) cells in neurodegenerative diseases, such as multiple sclerosis, Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis. However, the precise function of NK cells in these diseases remains ambiguous. The existence of two NK cell subsets, CD56bright and CD56dim NK cells, complicates the understanding of the contribution of NK cells in neurodegeneration as their functions within the context of neurodegenerative diseases may differ significantly. CD56bright NK cells are potent cytokine secretors and are considered more immunoregulatory and less terminally differentiated than their mostly cytotoxic CD56dim counterparts. Hence, this review focusses on NK cells, specifically on CD56bright NK cells, and their role in neurodegenerative diseases. Moreover, it explores the mechanisms underlying their ability to enter the central nervous system. By consolidating current knowledge, we aim to provide a comprehensive overview on the role of CD56bright NK cells in neurodegenerative diseases. Elucidating their impact on neurodegeneration may have implications for future therapeutic interventions, potentially ameliorating disease pathogenesis.

Ocrelizumab Concentration Is a Good Predictor of SARS-CoV-2 Vaccination Response in Patients with Multiple Sclerosis.

Ocrelizumab, an anti-CD20 monoclonal antibody, counteracts induction of humoral immune responses after severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) vaccinations in patients with multiple sclerosis (MS). We aimed to assess if serum ocrelizumab concentration measured at the time of vaccination could predict the humoral response after SARS-CoV-2 vaccination. In 52 patients with MS, we found ocrelizumab concentration at the time of vaccination to be a good predictor for SARS-CoV-2 IgG anti-RBD titers after vaccination (comparable to B-cell count). As the course of ocrelizumab concentration may be predicted using pharmacokinetic models, this may be a superior biomarker to guide optimal timing for vaccinations in B-cell depleted patients with MS. ANN NEUROL 2023;93:103-108.

The association between weight during early life and multiple sclerosis onset in a nationwide Dutch birth year cohort.

BACKGROUND: The relationship between being overweight during early life and disease course in multiple sclerosis (MS) is unresolved. We investigated the association between being overweight or obese during early life (childhood and adolescence) and MS case status, age of first symptom onset and onset type in people with MS (pwMS) of the same birth year. METHODS: We enrolled 363 PwMS and 125 healthy controls (HC) from Project Y, a Dutch population-based cross-sectional cohort study including all PwMS born in 1966 and age and sex-matched HC. The associations between weight during childhood and adolescence (non-overweight vs. overweight or obese) and MS, age at symptom onset and onset type (relapsing vs. progressive) were assessed using logistic and linear regressions. In addition, sex-separated associations were explored. RESULTS: Being overweight or obese during childhood (OR = 2.82, 95% CI 1.17-6.80) and adolescence (OR = 2.45, 95% CI 1.13-5.34) was associated with developing MS. Furthermore, being overweight or obese during adolescence was associated with a younger age of onset (ß = -0.11, p = 0.041). Of all 47 patients with a primary progressive (PP) onset type, only one patient (2.1%) was overweight or obese during childhood, whereas 45 patients with a relapsing remitting (RR) onset (14.3%) were overweight or obese during childhood (PP vs. RR p = 0.017; PP vs. HC p = 0.676; RR vs. HC, p = 0.015). However, using logistic regression analysis we did not find evidence of a significant association. CONCLUSION: In a nationwide population-based birth year cohort, being overweight or obese during childhood or adolescence is associated with MS prevalence and an earlier age of onset, but does not seem to associate with the type of onset.

Ocrelizumab concentration and antidrug antibodies are associated with B-cell count in multiple sclerosis.

BACKGROUND: The majority of patients with multiple sclerosis on ocrelizumab have B-cell depletion after standard interval dosing of 26 weeks. With B-cell-guided dosing patients receive their next dose when B-cell repopulation occurs. Prediction of B-cell repopulation using ocrelizumab concentrations could aid in personalising treatment regimes. The objectives of this study were to evaluate the association between ocrelizumab drug concentration, antidrug antibodies (ADAs) and CD19 B-cell count, and to define a cut-off ocrelizumab concentration for start of B-cell repopulation (defined by ≥10 CD19+ B cells/µL). METHODS: In this investigator-initiated prospective study, blood samples at various time points during ocrelizumab treatment were collected from a biobank. Serum ocrelizumab concentrations and ADAs were measured with two different assays developed for this study. Data were analysed using linear mixed effect models. An receiver operating characteristic (ROC) curve was used to determine a cut-off ocrelizumab concentration for start of B-cell repopulation (defined by ≥10 cells/µL). RESULTS: A total of 452 blood samples from 72 patients were analysed. Ocrelizumab concentrations were detectable up until 53.3 weeks after last infusion and ranged between <0.0025 and 204 µg/mL after 1-67 weeks. Ocrelizumab concentration was negatively associated with B-cell count, with body mass index identified as effect modifier. We found a cut-off value of 0.06 µg/mL for start of B-cell repopulation of ≥10 cells/µL. Ocrelizumab ADAs were detectable in four patients (5.7%) with corresponding low ocrelizumab concentrations and start of B-cell repopulation. CONCLUSIONS: Serum ocrelizumab concentration was strongly associated with B-cell count. Measurement of ocrelizumab drug concentrations and ADAs could play an important role to further personalise treatment and predict the start of B-cell repopulation.

Decrease of natalizumab drug levels after switching from intravenous to subcutaneous administration in patients with multiple sclerosis.

BACKGROUND: Natalizumab is effective in the treatment of multiple sclerosis (MS). In 2021, the European Medicines Agency approved the subcutaneous (SC) variant of natalizumab which can be used instead of intravenous administration. However, the course of drug levels varies between administration routes, and the Food and Drug Administration rejected the request for approval of natalizumab SC for reasons that were not disclosed. Our objective was to evaluate the course of natalizumab trough drug levels in patients who switched from natalizumab intravenous to SC on various treatment intervals. METHODS: The NEXT-MS trial (N=382) investigates personalised treatment of natalizumab, in which infusion intervals are prolonged based on individual natalizumab trough drug levels. In 2021, an amendment was approved allowing participants to switch from intravenous to SC administration with frequent measurements of natalizumab drug levels and antidrug antibodies (ADAs). Results were compared with linear mixed model analyses. RESULTS: Until December 2022, 15 participants switched to SC natalizumab. Natalizumab drug levels with SC administration were on average 55% lower compared with intravenous administration (Exp (estimate) 0.45, 95% CI 0.39 to 0.53, p<0.001), leading to very low trough drug levels in three patients on extended treatment intervals. No natalizumab ADAs were detected during intravenous or SC treatment. None of the participants on natalizumab SC showed evidence of MS disease activity. CONCLUSIONS: Natalizumab trough drug levels can decrease after switching from natalizumab intravenous to SC administration. We advise to monitor trough drug levels in patients with low natalizumab drug levels during intravenous treatment, patients with higher body mass index or patients on extended treatment intervals who switch to SC administration of natalizumab.

Whole Exome Sequencing in Multi-Incident Families Identifies Novel Candidate Genes for Multiple Sclerosis.

Multiple sclerosis (MS) is a degenerative disease of the central nervous system in which auto-immunity-induced demyelination occurs. MS is thought to be caused by a complex interplay of environmental and genetic risk factors. While most genetic studies have focused on identifying common genetic variants for MS through genome-wide association studies, the objective of the present study was to identify rare genetic variants contributing to MS susceptibility. We used whole exome sequencing (WES) followed by co-segregation analyses in nine multi-incident families with two to four affected individuals. WES was performed in 31 family members with and without MS. After applying a suite of selection criteria, co-segregation analyses for a number of rare variants selected from the WES results were performed, adding 24 family members. This approach resulted in 12 exonic rare variants that showed acceptable co-segregation with MS within the nine families, implicating the genes MBP, PLK1, MECP2, MTMR7, TOX3, CPT1A, SORCS1, TRIM66, ITPR3, TTC28, CACNA1F, and PRAM1. Of these, three genes (MBP, MECP2, and CPT1A) have been previously reported as carrying MS-related rare variants. Six additional genes (MTMR7, TOX3, SORCS1, ITPR3, TTC28, and PRAM1) have also been implicated in MS through common genetic variants. The proteins encoded by all twelve genes containing rare variants interact in a molecular framework that points to biological processes involved in (de-/re-)myelination and auto-immunity. Our approach provides clues to possible molecular mechanisms underlying MS that should be studied further in cellular and/or animal models.

Myelin Quantification in White Matter Pathology of Progressive Multiple Sclerosis Post-Mortem Brain Samples: A New Approach for Quantifying Remyelination.

Multiple sclerosis (MS) is a demyelinating and neurodegenerative disease of the central nervous system (CNS). Repair through remyelination can be extensive, but quantification of remyelination remains challenging. To date, no method for standardized digital quantification of remyelination of MS lesions exists. This methodological study aims to present and validate a novel standardized method for myelin quantification in progressive MS brains to study myelin content more precisely. Fifty-five MS lesions in 32 tissue blocks from 14 progressive MS cases and five tissue blocks from 5 non-neurological controls were sampled. MS lesions were selected by macroscopic investigation of WM by standard histopathological methods. Tissue sections were stained for myelin with luxol fast blue (LFB) and histological assessment of de- or remyelination was performed by light microscopy. The myelin quantity was estimated with a novel myelin quantification method (MQM) in ImageJ. Three independent raters applied the MQM and the inter-rater reliability was calculated. We extended the method to diffusely appearing white matter (DAWM) and encephalitis to test potential wider applicability of the method. Inter-rater agreement was excellent (ICC = 0.96) and there was a high reliability with a lower- and upper limit of agreement up to -5.93% to 18.43% variation in myelin quantity. This study builds on the established concepts of histopathological semi-quantitative assessment of myelin and adds a novel, reliable and accurate quantitative measurement tool for the assessment of myelination in human post-mortem samples.

[Treatment of multiple sclerosis]. / Behandelmogelijkheden bij multiple sclerose.

Multiple sclerosis is a chronic inflammatory disease of the central nervous system, caused by an autoimmune reaction. Treatment options have largely increased over the years. In this article, we present two clinical cases. Patient A has a classic relapsing remitting course of multiple sclerosis with satisfactory effect on second line therapy. Patient B had a stable disease course until a new relapse occurred after the initiation of TNF-alpha blocking therapy because of Crohn's disease. The co-occurrence of multiple auto-immune diseases creates challenges, but also opportunities in choosing the right treatment strategy.

Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis.

BACKGROUND: Robust predictive models of clinical impairment and worsening in multiple sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies. OBJECTIVE: To evaluate whether machine learning (ML) methods can classify clinical impairment and predict worsening in people with MS (pwMS) and, if so, which combination of clinical and magnetic resonance imaging (MRI) features and ML algorithm is optimal. METHODS: We used baseline clinical and structural MRI data from two MS cohorts (Berlin: n = 125, Amsterdam: n = 330) to evaluate the capability of five ML models in classifying clinical impairment at baseline and predicting future clinical worsening over a follow-up of 2 and 5 years. Clinical worsening was defined by increases in the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk Test (T25FW), 9-Hole Peg Test (9HPT), or Symbol Digit Modalities Test (SDMT). Different combinations of clinical and volumetric MRI measures were systematically assessed in predicting clinical outcomes. ML models were evaluated using Monte Carlo cross-validation, area under the curve (AUC), and permutation testing to assess significance. RESULTS: The ML models significantly determined clinical impairment at baseline for the Amsterdam cohort, but did not reach significance for predicting clinical worsening over a follow-up of 2 and 5 years. High disability (EDSS ≥ 4) was best determined by a support vector machine (SVM) classifier using clinical and global MRI volumes (AUC = 0.83 ± 0.07, p = 0.015). Impaired cognition (SDMT Z-score ≤ -1.5) was best determined by a SVM using regional MRI volumes (thalamus, ventricles, lesions, and hippocampus), reaching an AUC of 0.73 ± 0.04 (p = 0.008). CONCLUSION: ML models could aid in classifying pwMS with clinical impairment and identify relevant biomarkers, but prediction of clinical worsening is an unmet need.

Association of Polygenic Risk Score With Lifetime Risk of Developing Multiple Sclerosis in a Population-Based Birth-Year Cohort.

BACKGROUND AND OBJECTIVES: More than 200 genetic variants have been associated with multiple sclerosis (MS) susceptibility. However, it is unclear to what extent genetic factors influence lifetime risk of MS. Using a population-based birth-year cohort, we investigate the effect of genetics on lifetime risk of MS. METHODS: In the Project Y study, we tracked down almost all persons with MS (pwMS) from birth year 1966 in the Netherlands. As control participants, we included non-MS participants from the Project Y cohort (born 1965-1967 in the Netherlands) and non-MS participants from the Amsterdam Dementia Cohort born between 1963 and 1969. Genetic variants associated with MS were determined in pwMS and control participants using genotyping or imputation methods. Polygenic risk scores (PRSs) based on variants and weights from the largest genetic study in MS were calculated for each participant and assigned into deciles based on the PRS distribution in the control participants. We examined the lifetime risk for each decile and the association between PRS and MS disease variables, including age at onset and time to secondary progression. RESULTS: MS-PRS was calculated for 285 pwMS (mean age 53.0 ± 0.9 years, 72.3% female) and 267 control participants (mean age 51.8 ± 3.2 years, 58.1% female). Based on the lifetime risk estimation, we observed that 1:2,739 of the women with the lowest 30% genetic risk developed MS, whereas 1:92 of the women with the top 10% highest risk developed MS. For men, only 1:7,900 developed MS in the lowest 30% genetic risk group, compared with 1:293 men with the top 10% genetic risk. The PRS was not significantly associated with age at onset and time to secondary progression in both sexes. DISCUSSION: Our results show that the lifetime risk of MS is strongly influenced by genetic factors. Our findings have the potential to support diagnostic certainty in individuals with suspected MS: a high PRS could strengthen a diagnosis, but especially a PRS from the lowest tail of the PRS distribution should be considered a red flag and could prevent misdiagnosing conditions that mimic MS.

Scanner-specific optimisation of automated lesion segmentation in MS.

BACKGROUND & OBJECTIVE: Automatic lesion segmentation techniques on MRI scans of people with multiple sclerosis (pwMS) could support lesion detection and segmentation in trials and clinical practice. However, knowledge on their reliability across scanners is limited, hampering clinical implementation. The aim of this study was to investigate the within-scanner repeatability and between-scanner reproducibility of lesion segmentation tools in pwMS across three different scanners and examine their accuracy compared to manual segmentations with and without optimization. METHODS: 30 pwMS underwent a scan and rescan on three MRI scanners. GE Discovery MR750 (3.0 T), Siemens Sola (1.5 T) and Siemens Vida (3.0 T)). 3D-FLuid Attenuated Inversion Recovery (3D-FLAIR) and 3D T1-weighted scans were acquired on each scanner. Lesion segmentation involved preprocessing and automatic segmentation using the Lesion Segmentation Toolbox (LST) and nicMSlesions (nicMS) as well as manual segmentation. Both automated segmentation techniques were used with default settings, and with settings optimized to match manual segmentations for each scanner specifically and combined for the three scanners. LST settings were optimized by adjusting the threshold to improve the Dice similarity coefficient (DSC) for each scanner separately and a combined threshold for all scanners. For nicMS the last layers were retrained, once with the multi-scanner data to represent a combined optimization and once separately for each scanner for scanner specific optimization. Volumes and counts were extracted. DSC was calculated for accuracy, and reliability was assessed using intra-class correlation coefficients (ICC). Differences in DSC between software was tested with a repeated measures ANOVA and when appropriate post-hoc paired t-tests using Bonferroni correction. RESULTS: Scanner-specific optimization significantly improved DSC for LST compared to default and combined settings, except for the GE scanner. NicMS showed significantly higher DSC for both the scanner-specific and combined optimization than default. Within-scanner repeatability was excellent (ICC>0.9) for volume and counts. Between-scanner ICC for volume between Vida and Sola was higher (0.94-0.99) than between GE MR750 and Vida or Sola (0.18-0.93), with improved ICCs for nicMS scanner-specific (0.87-0.93) compared to others (0.18-0.79). This was not present for Sola vs. Vida where all ICCs were excellent (>0.94). CONCLUSION: Scanner-specific optimization strategies proved effective in mitigating inter-scanner variability, addressing the issue of insufficient reproducibility and accuracy found with default settings.

9-HODE associates with thalamic atrophy and predicts white matter damage in multiple sclerosis.

BACKGROUND: Multiple sclerosis (MS) is characterized by extensive tissue damage leading to a range of complex symptoms, including physical disability and cognitive dysfunction. Recent work has indicated the clinical relevance of bioactive lipid mediators (LMs), which are known to orchestrate inflammation and its resolution and are deregulated in MS. However, it is unknown whether LM profiles relate to white matter (WM) damage. OBJECTIVES: To investigate the potential association between plasma-derived LMs and MRI-quantified WM damage using fractional anisotropy (FA) and grey matter (GM) atrophy in dimethyl fumarate-treated relapsing remitting MS (RRMS) patients. METHODS: Severity of FA-based WM damage and GM atrophy was determined in RRMS patients (n = 28) compared to age- and sex-matched controls (n = 31) at treatment initiation (baseline) and after 6 months. Plasma LMs were assessed using HPLC-MS/MS and baseline LMs were correlated to changes in FA and brain volumes. RESULTS: We observed significant WM damage in RRMS patients (mean age 41.4 [SD 9.1]) at baseline and follow-up (z-score=-0.33 and 0.31, respectively) compared to controls (mean age 41.9 [SD 9.5]; p < 0.001 for both comparisons). Patients with severe WM damage showed a decline of thalamic volume (p = 0.02), and this decline correlated (r = 0.51, p < 0.001) with lower baseline levels of 9-HODE. This LM also predicted FA worsening (beta = 0.14, p < 0.001) over time at 6 months. CONCLUSION: Despite the relatively small sample size, lower baseline levels of the LM 9-HODE correlated with more thalamic atrophy and predicted subsequent worsening of WM damage in RRMS patients.

Clinical risk stratification: Development and validation of the DAAE score, a tool for estimating patient risk of transition to secondary progressive multiple sclerosis.

BACKGROUND: Because secondary progressive multiple sclerosis (SPMS) is associated with worse prognosis, early predictive tools are needed. We aimed to use systematic literature review and advanced methods to create and validate a clinical tool for estimating individual patient risk of transition to SPMS over five years. METHODS: Data from the Jacobs Multiple Sclerosis Center (JMSC) and the Multiple Sclerosis Center Amsterdam (MSCA) was collected between 1994 and 2022. Participants were relapsing-remitting adult patients at initial evaluation. We created the tool in four stages: (1) identification of candidate predictors from systematic literature review, (2) ordinal cutoff determination, (3) feature selection, (4) feature weighting. RESULTS: Patients in the development/internal-validation/external-validation datasets respectively (n = 787/n = 522/n = 877) had a median age of 44.1/42.4/36.6 and disease duration of 7.7/6.2/4.4 years. From these, 12.6 %/10.2 %/15.4 % converted to SPMS (median=4.9/5.2/5.0 years). The DAAE Score was named from included predictors: Disease duration, Age at disease onset, Age, EDSS. It ranges from 0 to 12 points, with risk groups of very-low=0-2, low=3-7, medium=8-9, and high≥10. Risk of transition to SPMS increased proportionally across these groups in development (2.7 %/7.4 %/18.8 %/40.2 %), internal-validation (2.9 %/6.8 %/26.8 %/36.5 %), and external-validation (7.5 %/9.6 %/22.4 %/37.5 %). CONCLUSION: The DAAE Score estimates individual patient risk of transition to SPMS consistently across datasets internationally using clinically-accessible data. With further validation, this tool could be used for clinical risk estimation.

Digital outcome measures are associated with brain atrophy in patients with multiple sclerosis.

BACKGROUND: Digital monitoring of people with multiple sclerosis (PwMS) using smartphone-based monitoring tools is a promising method to assess disease activity and progression. OBJECTIVE: To study cross-sectional and longitudinal associations between active and passive digital monitoring parameters and MRI volume measures in PwMS. METHODS: In this prospective study, 92 PwMS were included. Clinical tests [Expanded Disability Status Scale (EDSS), Timed 25 Foot Walk test (T25FW), 9-Hole Peg Test (NHPT), and Symbol Digit Modalities Test (SDMT)] and structural MRI scans were performed at baseline (M0) and 12-month follow-up (M12). Active monitoring included the smartphone-based Symbol Digit Modalities Test (sSDMT) and 2 Minute Walk Test (s2MWT), while passive monitoring was based on smartphone keystroke dynamics (KD). Linear regression analyses were used to determine cross-sectional and longitudinal relations between digital and clinical outcomes and brain volumes, with age, disease duration and sex as covariates. RESULTS: In PwMS, both sSDMT and SDMT were associated with thalamic volumes and lesion volumes. KD were related to brain, ventricular, thalamic and lesion volumes. No relations were found between s2MWT and MRI volumes. NHPT scores were associated with lesion volumes only, while EDSS and T25FW were not related to MRI. No longitudinal associations were found for any of the outcome measures between M0 and M12. CONCLUSION: Our results show clear cross-sectional correlations between digital biomarkers and brain volumes in PwMS, which were not all present for conventional clinical outcomes, supporting the potential added value of digital monitoring tools.

Glutamate gene polymorphisms predict brain volumes in multiple sclerosis.

BACKGROUND: Several genetic markers have been associated with multiple sclerosis (MS) susceptibility; however, uncovering the genetic aetiology of the complex phenotypic expression of MS has been more difficult so far. The most common approach in imaging genetics is based on mass-univariate linear modelling (MULM), which faces several limitations. OBJECTIVE: Here we apply a novel multivariate statistical model, sparse reduced-rank regression (sRRR), to identify possible associations of glutamate related single nucleotide polymorphisms (SNPs) and multiple MRI-derived phenotypes in MS. METHODS: Seven phenotypes related to brain and lesion volumes for a total number of 326 relapsing-remitting and secondary-progressive MS patients and a total of 3809 glutamate related and control SNPs were analysed with sRRR, which resulted in a ranking of SNPs in decreasing order of importance ('selection probability'). Lasso regression and MULM were used as comparative statistical techniques to assess consistency of the most important associations over different statistical models. RESULTS: Five SNPs within the NMDA-receptor-2A-subunit (GRIN2A) domain were identified by sRRR in association with normalized brain volume (NBV), normalized grey matter volume and normalized white matter volume (NMWM). The association between GRIN2A and both NBV and NWMV was confirmed in MULM and Lasso analysis. CONCLUSIONS: Using a novel, multivariate regression model confirmed by two other statistical approaches we show associations between GRIN2A SNPs and phenotypic variation in NBV and NWMV in this first exploratory study. Replications in independent datasets are now necessary to validate these findings.

Repair what is lost: Neuroprotection through neural stem cells in progressive MS.

Genchi et al.1 report the first phase 1 trial of neural stem cell transplantation in multiple sclerosis showing a reduction in gray matter atrophy. Results give hope for a new era of induced neuroprotection, especially in progressive multiple sclerosis.

Longitudinal Changes in Cognitive Test Scores in Patients With Relapsing-Remitting Multiple Sclerosis: An Analysis of the DECIDE Dataset.

BACKGROUND AND OBJECTIVES: Cognitive impairment is a common and impactful symptom of relapsing-remitting multiple sclerosis (RRMS). Cognitive outcome measures are often used in cross-sectional studies, but their performance as longitudinal outcome measures in clinical trials is not widely researched. In this study, we used data from a large clinical trial to describe change on the Symbol Digit Modalities Test (SDMT) and the Paced Auditory Serial Addition Test (PASAT) over up to 144 weeks of follow-up. METHODS: We used the data set from DECIDE (clinicaltrials.gov identifier NCT01064401), a large randomized controlled RRMS trial to describe change on the SDMT and PASAT over 144 weeks of follow-up. We compared change on these cognitive outcomes with change on the timed 25-foot walk (T25FW), a well-established physical outcome measure. We investigated several definitions for clinically meaningful change: any change, 4-point change, 8-point change, and 20% change for the SDMT, any change, 4-point change, and 20% change for the PASAT, and 20% change for the T25FW. RESULTS: DECIDE included 1,814 trial participants. SDMT and PASAT scores steadily improved throughout follow-up: the SDMT from a mean 48.2 (SD, 16.1) points at baseline to 52.6 (SD 15.2) at 144 weeks and the PASAT from 47.0 (SD 11.3) at baseline to 50.0 (SD 10.8) at 144 weeks. This improvement in scores is most likely due to a practice effect. Throughout the trial, participants were more likely to experience improvement than worsening of their SDMT and PASAT performance, whereas the number of worsening events on the T25FW steadily increased. Changing the definition of clinically meaningful change for the SDMT and PASAT or using a 6-month confirmation changed the overall number of worsening or improvement events but did not affect the overall behavior of these measures. DISCUSSION: Our findings suggest that the SDMT and PASAT scores do not accurately reflect the steady cognitive decline that people with RRMS experience. Both outcomes show postbaseline increases in scores, which complicates the interpretation of these outcome measures in clinical trials. More research into the size of these changes is needed before recommending a general threshold for clinically meaningful longitudinal change.

The role of diet in multiple sclerosis onset and course: results from a nationwide retrospective birth-year cohort.

OBJECTIVE: To examine (1) the association between childhood diet and developing MS, age of onset and onset type and (2) the association between diet at age 50 and disability and MRI volumes in people with MS (PwMS). METHODS: The study enrolled 361 PwMS born in 1966 and 125 age- and sex-matched healthy controls (HCs). Information on individual dietary components (fruit, vegetables, red meat, oily fish, whole-grain bread and candy, snacks and fast food) and MS risk factors at the age of 10 and 50 years were collected using questionnaires. Overall diet quality score was calculated for each participant. Multivariable regression analyses were used to evaluate the association between diet at childhood and developing MS, age of onset and onset type and to evaluate diet at age 50, disability and MRI outcomes. RESULTS: Poorer overall diet quality and individual dietary components during childhood (less whole-grain bread, more candy, snacks and fast food and oily fish) were associated with developing MS and onset type (all p < 0.05), but not with the age of onset. Fruit consumption at age 50 was associated with lower disability (Q3 vs. Q1: -0.51; 95% CI: -0.89 to -0.13). Furthermore, several individual dietary components at age 50 were associated with MRI volumetric measures. Higher-diet quality at age 50 was only associated with lower lesion volumes in PwMS (Q2 vs. Q1: -0.3 mL; 95% CI: -0.5 to -0.02). INTERPRETATION: We demonstrate significant associations between dietary factors in childhood and developing MS, age of onset and onset type and between dietary factors at age 50 and disability and MRI-derived volumes.

Adipokines in multiple sclerosis patients are related to clinical and radiological measures.

BACKGROUND: An imbalance of adipokines, hormones secreted by white adipose tissue, is suggested to play a role in the immunopathology of multiple sclerosis (MS). In people with MS (PwMS) of the same age, we aimed to determine whether the adipokines adiponectin, leptin, and resistin are associated with MS disease severity. Furthermore, we aimed to investigate whether these adipokines mediate the association between body mass index (BMI) and MS disease severity. METHODS: Adiponectin, resistin, and leptin were determined in serum using ELISA. 288 PwMS and 125 healthy controls (HC) were included from the Project Y cohort, a population-based cross-sectional study of people with MS born in the Netherlands in 1966, and age and sex-matched HC. Adipokine levels and BMI were related to demographic, clinical and disability measures, and MRI-based brain volumes. RESULTS: Adiponectin levels were 1.2 fold higher in PwMS vs. HC, especially in secondary progressive MS. Furthermore, we found a sex-specific increase in adiponectin levels in primary progressive (PP) male patients compared to male controls. Leptin and resistin levels did not differ between PwMS and HC, however, leptin levels were associated with higher disability (EDSS) and resistin strongly related to brain volumes in progressive patients, especially in several grey matter regions in PPMS. Importantly, correction for BMI did not significantly change the results. CONCLUSION: In PwMS of the same age, we found associations between adipokines (adiponectin, leptin, and resistin) and a range of clinical and radiological metrics. These associations were independent of BMI, indicating distinct mechanisms.

Neuroaxonal and Glial Markers in Patients of the Same Age With Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: The specificity of novel blood biomarkers for multiple sclerosis (MS)-related neurodegeneration is unclear because neurodegeneration also occurs during normal aging. To understand which aspects of neurodegeneration the serum biomarkers neurofilament light (sNfL), serum glial fibrillary acidic protein (sGFAP), and serum contactin-1 (sCNTN1) reflect, we here explore their cross-sectional association with disability outcome measures and MRI volumes in a unique cohort of people with MS (PwMS) of the same age. METHODS: sNfL, sGFAP (both singe-molecule array technology) and sCNTN1 (Luminex) were measured in serum samples of 288 PwMS and 125 healthy controls (HCs) of the Project Y cohort, a population-based cross-sectional study of PwMS born in the Netherlands in 1966 and age-matched HC. RESULTS: sNfL (9.83 pg/mL [interquartile range {IQR}: 7.8-12.0]) and sGFAP (63.7 pg/mL [IQR: 48.5-84.5]) were higher in PwMS compared with HC (sNfL: 8.8 pg/mL [IQR: 7.0-10.5]; sGFAP: 51.7 pg/mL [IQR: 40.1-68.3]) (p < 0.001), whereas contactin-1 (7,461.3 pg/mL [IQR: 5,951.8-9,488.6]) did not significantly differ between PwMS compared with HC (7,891.2 pg/mL [IQR: 6,120.0-10,265.8]) (p = 0.068). sNfL and sGFAP levels were 1.2-fold higher in secondary progressive patients (SPMS) compared with relapsing remitting patients (p = 0.009 and p = 0.043). Stratified by MS subtype, no relations were seen for CNTN1, whereas sNfL and sGFAP correlated with the Expanded Disability Status Scale (ρ = 0.43 and ρ = 0.39), Nine-Hole Peg Test, Timed 25-Foot Walk Test, and Symbol Digit Modalities Test (average ρ = 0.38) only in patients with SPMS. Parallel to these clinical findings, correlations were only found for sNfL and sGFAP with MRI volumes. The strongest correlations were observed between sNfL and thalamic volume (ρ = -0.52) and between sGFAP with deep gray matter volume (ρ = - 0.56) in primary progressive patients. DISCUSSION: In our cohort of patients of the same age, we report consistent correlations of sNfL and sGFAP with a range of metrics, especially in progressive MS, whereas contactin-1 was not related to clinical or MRI measures. This demonstrates the potential of sNfL and sGFAP as complementary biomarkers of neurodegeneration, reflected by disability, in progressive MS.