Multiple Sclerosis Journal最新文献

Background: Colitis has been reported with some anti-CD20 therapies in multiple sclerosis (MS), but not previously with ofatumumab.

Objectives: To report the first case of ofatumumab-associated colitis in MS and discuss its implications.

Methods: Case report.

Results: A 56-year-old female with relapsing-remitting multiple sclerosis (RRMS) developed severe colitis 3 months after initiating ofatumumab, requiring hospitalization and treatment discontinuation.

Conclusion: This case suggests a potential class effect of anti-CD20 therapies, including ofatumumab, in relation to colitis in MS. Clinicians should monitor for gastrointestinal symptoms in MS patients receiving any anti-CD20 therapy.

Background: Little is known about how multiple sclerosis (MS) presents in Hispanic/Latinx (HL) people with MS (pwMS).

Objective: Compare age at onset (AAO) and onset severity between HL versus non-Hispanic White (NHW) pwMS.

Methods: A cross-sectional study leveraged the MS PATHS registry spanning seven US tertiary care institutions. HL was subcategorized as HL White (HLW) and HL Other (HLO; all other races). Multivariable models examined relationships between ethnoracial variables and AAO and self-reported presenting disease course. Models were repeated restricting to those born ⩾1970.

Results: The study population included 8231 pwMS, including 540 HL (200 HLW, 340 HLO). The sex distribution did not differ across ethnoracial subgroups. From the statistical models (1) HLO pwMS had an earlier AAO and a higher prevalence of initial progressive disease course than NHW pwMS; (2) among all HL pwMS, irrespective of race, AAO did not differ by sex or between relapsing and progressive MS at onset. In younger HLO adults (born ⩾1970), those with progressive MS at onset had an earlier AAO than those with relapsing MS; and (3) in HL pwMS there was no sex-bias in presenting disease course.

Discussion: Distinct differences in the presentation of MS in HL compared with NHW individuals were observed.

Background: Exercise is a safe and effective way to improve physical function in people with multiple sclerosis (PWMS).

Objectives: This study aimed to perform a head-to-head study of the effects of aerobic and resistance training on physical capacity and physical function.

Methods: A multicentre randomized controlled trial with 150 participants was conducted. Participants were randomized into 12 weeks of either aerobic training (AT; n = 62), resistance training (RT; n = 57), or usual care (UC; n = 31). The primary outcome was physical function (measured as a composite score of the 6-minute walk test and five-time sit-to-stand). Secondary outcomes were aerobic capacity (VO₂peak), maximal muscle strength (MVC), and self-reported walking ability.

Results: Participants had a mean age of 45.5 (8.8), an expanded disability status scale (EDSS) of 2.8 (1.5), and 75% were female. Physical function did not increase in AT versus UC 0.08 [-0.16; 0.33] (mean (95% CI)) nor in RT versus UC 0.09 [-0.15; 0.34].VO₂peak increased in AT versus UC by 4.1 [2.0; 6.3] mL O₂/min/kg and in AT versus RT by 2.7 [1.1; 4.3], but not in RT versus UC 1.4 [-0.6; 3.5]. MVC increased in RT versus UC by 0.25 [0.01; 0.48] Nm/kg, but not in RT versus AT 0.17 [-0.02; 0.36] or AT versus UC 0.08 [-0.16; 0.31]).

Conclusion: AT and RT elicited improvements in physical capacity in PWMS. However, these improvements only moderately translated into improvements in physical function.Clinicaltrials.gov (NCT04913012)https://clinicaltrials.gov/study/NCT04913012.

Background: Fatigue is a major "invisible" symptom in people with multiple sclerosis (PwMS), which may affect speech. Automated speech analysis is an objective, rapid tool to capture digital speech biomarkers linked to functional outcomes.

Objective: To use automated speech analysis to assess multiple sclerosis (MS) fatigue metrics.

Methods: Eighty-four PwMS completed scripted and spontaneous speech tasks; fatigue was assessed with Modified Fatigue Impact Scale (MFIS). Speech was processed using an automated speech analysis pipeline (ki elements: SIGMA speech processing library) to transcribe speech and extract features. Regression models assessed associations between speech features and fatigue and validated in a separate set of 30 participants.

Results: Cohort characteristics were as follows: mean age 49.8 (standard deviation (SD) = 13.6), 71.4% female, 85% relapsing-onset, median Expanded Disability Status Scale (EDSS) 2.5 (range: 0-6.5), mean MFIS 27.6 (SD = 19.4), and 30% with MFIS > 38. MFIS moderately correlated with pitch (R = 0.32, p = 0.005), pause duration (R = 0.33, p = 0.007), and utterance duration (R = 0.31, p = 0.0111). A logistic model using speech features from multiple tasks accurately classified MFIS in training (area under the curve (AUC) = 0.95, R² = 0.59, p < 0.001) and test sets (AUC = 0.93, R² = 0.54, p = 0.0222). Adjusting for EDSS, processing speed, and depression in sensitivity analyses did not impact model accuracy.

Conclusion: Fatigue may be assessed using simple, low-burden speech tasks that correlate with gold-standard subjective fatigue measures.

Background: Cognitive decline in multiple sclerosis (MS) is associated with neuro-axonal loss, quantifiable by optical coherence tomography (OCT). Associations between OCT measures and cognition in relapsing-remitting MS (RRMS) remain incompletely investigated, particularly the added value of OCT when combined with magnetic resonance imaging (MRI). We investigated the contributions of OCT and MRI while applying stringent criteria to control for subclinical optic neuropathy.

Methods: In this cross-sectional study, 137 RRMS patients underwent OCT, Brief International Cognitive Assessment for MS (BICAMS), Expanded Disability Status Scale (EDSS) and brain MRI (lesion load, grey and white matter volume); associations were explored using linear regression models.

Results: RRMS patients (aged 40.88 ± 10.6 years; disease duration 7.95 ± 7.39 years; EDSS 2; 0-6.5) were studied. Of BICAMS, 50.36% showed impaired Symbol Digit Modalities Test (SDMT), 37.23% impaired Brief Visuospatial Memory Test and 5.11% impaired California Verbal Learning and Memory Test; better SDMT performance was associated with thicker ganglion cell-inner plexiform (GCIPL) layers for eyes unaffected by optic neuritis (B = 0.23, 95% CI = (0.01-0.44), p = 0.03), but not when MRI measures were included (B = 0.18, CI = (-0.03 to 0.38), p = 0.09).

Conclusion: GCIPL thinning correlates with SDMT, supporting OCT as a biomarker of cognitive dysfunction. However, GCIPL did not uniquely predict SDMT performance when including MRI measures, suggesting limited utility of OCT in predicting cognitive performance over MRI in RRMS.

Background: Paramagnetic rim lesions (PRL) are valuable for diagnosing and prognosing multiple sclerosis (MS) and detectable at 7T and 3T MRI. For translation into clinical practice, it is essential assessing their visibility on 1.5T clinical scanners.

Objective: To evaluate the reliability of detecting PRL using commercially available susceptibility-weighted imaging (SWI) at 1.5 versus 3T MRI.

Methods: SWI images were obtained in 20 people with MS at 1.5T and 3T MRI, with an average scan interval of 1.1 years. Only stable, non-enhancing lesions visible on both scans were analyzed. PRL at 3T were identified by two expert raters using NAIMS PRL criteria and used as a reference. Four raters, blinded to 3T results, assessed PRL at 1.5T. Discrepancies were resolved by consensus.

Results: PRL were identified in 16 of 20 patients. At 3T, 95 PRL were identified by consensus (mean 5 PRL per patient, range 0-30). Blinded to 3T scans, 82% of PRL were visible at 1.5T (78 of 95 PRL). Interrater reliability was "almost perfect" for both 1.5 and 3T scans. Raters accurately classified all patients as having ⩾1PRL or not at 1.5T.

Conclusion: The majority of PRL are detectable at 1.5T without significantly reducing the specificity of PRL identification or increasing the detection of pseudo-PRL. This may facilitate their clinical use in MS diagnosis and prognosis.

The past 25 years have brought extraordinary advances in our understanding of MS pathogenesis and the subsequent development of effective therapies. Collaborative genetics efforts have uncovered the association of 236 common DNA variants with disease susceptibility and the first association with disease severity, paving the way to more effective therapies, particularly for progressive forms of the disease. In parallel, and in addition to established environmental disease triggers or modifiers, new collaborative work has revealed new associations with components of the gut microbiome. This research opened a new and exciting prospect for exploring the gut-brain axis, with the potential to also provide new pharmacologic targets and diet-based therapies. Finally, with the availability of massive amounts of information and unprecedented computer power, a new wave of artificial intelligence (AI)-based research is sprawling. These investigations will result in statistically powerful predictive models to identify individuals at risk even years before the disease is clinically apparent. Furthermore, using approaches like semantic representation and causal inference, some of these approaches will be explainable in biomedical terms, thus making them trusted and facilitating their implementation in the clinical setting. The common thread that characterizes all of these advances is multi-disciplinary collaboration among scientists in the form of formal consortia, working groups, or ad hoc partnerships. This may be the "secret sauce" of modern science and the best strategy to stop, restore, and end MS.

Background: Measuring brain volume changes over time is an objective and dependable surrogate marker for the pathological processes that damage the brain in relapsing-remitting multiple sclerosis (RRMS). These measures are particularly valuable for monitoring the long-term impact of immunomodulatory treatments such as cladribine.

Objectives: To evaluate the long-term impact of oral cladribine treatment on brain volume loss in patients with RRMS.

Methods: This real-world study processed magnetic resonance imaging (MRI) scans using FreeSurfer's recon-all-clinical pipeline leveraging SynthSeg for brain segmentation. Piecewise linear regression was used to analyze brain atrophy changes over 4.5 years before and after cladribine treatment and estimate the time breakpoint of atrophy rate change.

Results: A total of 448 MRI exams from 102 RRMS patients were analyzed. Before the initiation of cladribine treatment, brain atrophy rates were significantly steep with an α1 slope between -1.27 and -0.62 for the Thalamus, DGM, Subcortical GM, Cerebral WM, and BP. Over 2 years after treatment, breakpoints marked a shift in atrophy rates, with post-breakpoint slopes (α2) becoming non-significant, reflecting stabilization of brain atrophy.

Conclusions: Cladribine treatment in highly active RRMS patients protects the brain from atrophy, with stabilization occurring over 2 years after initiation. The extended observation period highlights its sustained benefits compared with shorter clinical trials.