Multiple Sclerosis Journal

The first Association of British Neurologists (ABN) UK multiple sclerosis (MS) pregnancy guidelines were published in 2019. Along with new disease-modifying treatments, significant new data have since become available, resulting in label changes and recognition of class effects. Alongside this, there has been increasing recognition of the importance of family planning considerations in treatment paradigms in MS.

We set out to update the ABN UK MS Pregnancy guidance with a systematic literature search, with updated guidance informed by multidisciplinary input from across neurology, obstetric medicine, pharmacy and specialist nurses.

Key updates include consideration of disease-modifying therapy mechanism and durability of action when discussing treatment approaches around pregnancy, alongside considering the impact of treatment withdrawal on relapses during pregnancy and in the postpartum period. Monoclonal antibody transfer into breast milk is generally accepted to be low, and so treatment during lactation can be considered. Active discussion around vaccination strategies during pregnancy and of the neonate is required, with vaccines generally considered safe. With active treatment strategies that take these factors into account, women can be reassured regarding disease control during pregnancy.

Data sources remain limited, and further dedicated real-world studies that capture the full range of outcomes required to inform risk–benefit discussions are needed. These require collaboration and infrastructure to support the delivery of high-quality care to all women with MS considering pregnancy.

The revised McDonald criteria shifted toward the recognition of the radiologically isolated syndrome (RIS) as the first phase of the multiple sclerosis (MS) spectrum.

To characterize differences between RIS individuals, early MS patients, and healthy controls (HCs) using a high-precision clinical assessment tool based on digital technology.

We performed a multicentric, cross-sectional study involving RIS, early MS patients, and HC. Subjects were assessed using Neuraccure, an iPad application capable of detecting subtle abnormalities in four neurological functions: hand coordination, low-contrast vision, reaction time, and eye movements.

In total, 565 individuals were included (MS: 255, RIS: 146, HC: 164). HC performed better than RIS and MS across all digital measures (p < 0.0001 to 0.03). There was no statistical difference between RIS and MS patients, except for the coordination test, which was slightly worse in MS patients (p = 0.03). The receiver operating characteristic (ROC) analysis indicated that the presence of at least two impaired functions could detect RIS and MS from HC with 83.2% sensitivity and 84.3% specificity. A higher number of impaired functions were associated with lower brain magnetic resonance imaging (MRI) volumes.

High-precision neurological evaluation can distinguish HC from RIS and MS at an individual scale with a good performance.

The prodromal phase of multiple sclerosis (MS) is increasingly recognized, but most studies have focused on isolated symptoms or static comorbidity counts, leaving the evolving structure of pre-onset disease burden underexplored.

To characterize dynamic disease trajectories preceding MS onset through longitudinal network modeling.

Health data from 10,273 MS patients and 47,167 matched controls in Sweden were analyzed. Disease co-occurrence networks were constructed for three pre-onset windows (0–5, 5–10, 10–15 years), with comparisons of centrality, clustering, and path length. Rewiring scores captured structural shifts, while Markov clustering and trajectory mapping identified comorbidity communities.

MS networks were denser, more clustered, and showed shorter path lengths than controls, reflecting higher systemic interconnectivity. Psychiatric and metabolic diagnoses, especially depression, anxiety, diabetes, and abdominal pain, were hubs that gained prominence over time. Distinct clusters, including neuropsychiatric-toxicological and immune-endocrine constellations, were observed only in MS. Rewiring analysis revealed significant topological shifts in key diagnoses, such as inflammatory central nervous system disorders and substance use, as onset approached.

MS is preceded by dynamic reorganization of the comorbidity landscape, marked by increasing connectivity and rewired hubs. This framework highlights systemic disruption before diagnosis and provides a novel, network-based tool for studying prodromes in complex disorders.

Little is known about the prodrome in pediatric-onset multiple sclerosis (POMS), especially potential age and sex differences.

To compare annual hospitalization and physician visit rates overall, and for physician visits, examine sex- and age-group (<12, 12–15, 16 to <18 years) differences, up to 18 years pre-first demyelinating event (pre-index) in 451 POMS and 1420 matched non–multiple sclerosis (MS) individuals.

Using Ontario administrative data (1991–2020), we estimated rate ratios (RRs) by visit-related diagnosis, sex, and age using over-dispersed-Poisson models.

The POMS cohort showed elevated rates by year 1 pre-index (“year −1”), for ill-defined, other-health-contact, mental-, and respiratory-related hospitalizations (RRs ⩾ 3.6). Elevated physician visits began at year −14 for respiratory (RRs ⩾ 1.3), year −13 for endocrine (RRs ⩾ 2.4) and injury-related (RRs ⩾ 1.2), year −12 for ill-defined (RRs ⩾ 1.3), and year −11 for nervous system (RRs ⩾ 4.0) and mental-related (RRs ⩾ 2.0). Nervous system visits showed the largest sex-gap; males with (vs without) MS had elevated RRs from year −12 and females from year −6; both peaked the year pre-index (males: RR = 47.2; 95% confidence interval (CI): 17.3–128.3; females: RR = 17.0; 95% CI: 8.9–32.3). Among 12- to 15-year-olds, elevated rates were sustained for respiratory-related (from year −12, except year −5), injury-related, and ill-defined (from year −13); (all RR ⩾ 1.3), while findings were more sporadic in the other age groups.

Findings suggest prolonged, organ-specific healthcare use pre-POMS, with some sex- and age-related differences indicating pre-onset disease heterogeneity.

Monitoring radiologic disease activity (RDA) is standard of care in multiple sclerosis (MS) because new lesions on magnetic resonance imaging (MRI) are associated with adverse outcomes and frequently prompt treatment reassessment and optimization. Coregistration-fusion comparison (CF) is more sensitive than conventional side-by-side comparison (CS) for detecting new lesions.

To apply CF to identify CS-missed RDA on brain MRIs originally reported as “stable” and to evaluate whether CS-missed RDA predicts future disease activity.

This retrospective cohort included 314 people with MS (pwMS) with three consecutive brain MRIs: previous MRI (t₁), index MRI (t₂; reported “stable” on CS), and subsequent MRI (t₃). CF was applied to three-dimensional Fluid-Attenuated Inversion Recovery (FLAIR) to identify CS-missed new lesions on t₂ versus t₁. Future RDA was defined as ⩾1 new lesion on t₃ versus t₂. Clinical disease activity (CDA) was defined as clinical relapse and/or confirmed disability progression during follow-up after t₂.

CF identified 183 CS-missed new lesions in 65/314 pwMS (20.7%). Future RDA (70.8% vs. 16.1%; p < 0.001) and CDA (20.0% vs. 10.0%; p = 0.028) were more frequent in the CS-missed lesion group. Relapse and disability progression, when analyzed separately, did not differ between groups. CS-missed RDA independently predicted future RDA (adjusted odds ratio (aOR) = 10.43; 95% confidence interval (CI) = 5.31–20.46, p < 0.001) and CDA (aOR = 2.49; 95% CI = 1.10–5.65, p = 0.029). Each additional missed lesion at t₂ was associated with more new lesions at t₃ (incidence rate ratio (IRR) = 1.205; 95% CI = 1.184–1.226, p < 0.001).

CF reclassified one in five pwMS reported as “stable” on CS as having CS-missed RDA, which predicted future disease activity.

To identify baseline clinical, structural, and functional magnetic resonance imaging (MRI) features predicting progression independent of relapse and magnetic resonance imaging activity (PIRMA) in multiple sclerosis (MS).

We included patients from the Italian Neuroimaging Network Initiative who showed no clinical or MRI activity at 5-year follow-up. PIRMA progressors versus stable patients were defined by confirmed Expanded Disability Status Scale (EDSS) progression. Baseline clinical features, white matter (WM) lesion, WM, cortical and deep gray matter (GM) volumes, C2–C3 spinal cord area, and functional connectivity (FC) from nine resting-state networks (RSNs) were compared. Step-wise logistic regressions tested PIRMA predictors among clinical and structural MRI features, RSNs, and kernel principal component analysis (k-PCA) characteristics.

Of 208 patients, 99 were excluded for clinical (n = 30) and MRI activity (n = 69). Among 109, 33% experienced PIRMA. PIRMA progressors were older, more disabled, had higher WM lesion volume, GM atrophy, and FC alterations. Logistic regressions identified higher EDSS (p < 0.001), age (p = 0.02), cortical atrophy (p = 0.04), and FC alterations as predictors (all p ⩽ 0.02). Six k-PCA components emerged; four (linked to GM atrophy, FC decrements, age, EDSS) predicted PIRMA (pseudo-R²= 0.61).

PIRMA is linked to aging, GM atrophy, and disrupted FC, highlighting the value of integrating structural and functional MRI markers to detect silent progression in MS.

Gene–environment interactions between smoking and HLA genotypes have been reported in multiple sclerosis (MS) susceptibility, although their relevance beyond disease onset remains unclear.

To examine whether the effect of smoking on disability progression differs according to HLA-A*02:01 and HLA-DRB1*15:01 status.

Patients from two population-based case–control cohorts were classified by smoking status at diagnosis and by HLA-A*02:01 and HLA-DRB1*15:01 status and were followed for up to 15 years through the Swedish MS registry (n = 6807). Cox regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) for 24-week confirmed disability worsening (CDW) and time to Expanded Disability Status Scale (EDSS) 3, 4, and 6. Interaction was assessed on the additive scale.

Compared with HLA-A*02:01-positive non-smokers, smoking at diagnosis was associated with a higher risk of disability progression primarily among individuals who lacked HLA-A*02:01, with consistently elevated risks of CDW (HR = 1.15, 95% CI = 1.06–1.26), EDSS 3 (HR = 1.26, 95% CI = 1.08–1.47), and EDSS 4 (HR = 1.50, 95% CI = 1.25–1.79). No clear effect of smoking was observed among HLA-A*02:01 carriers, and no evidence of interaction was detected between smoking and HLA-DRB1*15:01.

These findings suggest that the impact of smoking on MS progression varies according to immunogenetic background.

Smokers with multiple sclerosis (MS) experience worse disease, yet underlying mechanisms remain unknown. Smoking disrupts bile acid and tryptophan metabolism in non-MS populations; both pathways involve host–microbiome co-metabolism and have been linked to MS.

Determine whether smoking perturbs these metabolic pathways in MS and whether such alterations statistically mediate smoking’s effect on MS severity.

We analyzed serum bile acid, tryptophan, and tobacco-related metabolites across four independent MS cohorts (N = 266) using discovery-replication analyses. Mixed-effects regression assessed replicating associations with current smoking and nicotine exposure. Mediation analyses tested if replicating metabolites were potential mediators between smoking and MS severity. Hypothesis-generating metagenomic analyses explored smoking-associated gut–microbial shifts and metabolite correlations.

Current smokers and nicotine-exposed MS subjects had reductions in bile acids and tryptophan metabolites, notably indolepropionate, a neuroprotective, anti-inflammatory gut–microbial metabolite. Lower indolepropionate statistically mediated ~20% of smoking’s adverse effect on MS severity. Metagenomic analyses identified potential smoking-enriched MS-linked taxa, and that indolepropionate broadly co-occurs with microbial networks (e.g. Lachnoclostridium appeared inversely associated with indolepropionate in smokers with MS).

Tobacco exposure disrupts host–microbiome tryptophan and bile acid metabolism in persons with multiple sclerosis, with indolepropionate depletion partially mediating disease severity, highlighting a potential mechanistic pathway warranting further investigation in MS smokers.