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Multiple sclerosis (MS) is a chronic, immune-mediated disorder of the central nervous system, increasingly recognized as a disease continuum that begins years before the first neurological event. Genetic susceptibility, environmental exposures, and silent neuroinflammation contribute to early disease activity. Recent studies have highlighted a preclinical phase that includes both a biological stage, characterized by elevated biomarkers such as serum neurofilament light chain up to 10 years before onset, and a prodromal phase, marked by subtle but measurable symptoms. Population-based cohorts consistently show increased healthcare use, higher prevalence of psychiatric and cognitive disturbances, fatigue, pain, and gastrointestinal disorders years before diagnosis, which may represent prodromal symptoms. Radiologically isolated syndrome (RIS), defined by incidental demyelinating lesions in asymptomatic individuals, represents the visible form of this phase and provides a unique opportunity to study the transition to clinical disease. Approximately half of RIS patients develop MS within a decade, with predictors including younger age, male sex, CSF oligoclonal bands, and spinal cord involvement. Recent randomized controlled trials demonstrated that early use of disease-modifying therapies in RIS significantly reduces conversion risk. Defining the preclinical and prodromal phases of MS offers a major opportunity to refine risk stratification, enable earlier intervention, and ultimately prevent or delay the onset of clinically definite MS.

Multiple sclerosis (MS) is a chronic, inflammatory, and degenerative disease of the central nervous system (CNS). Inflammation is observed in all stages of MS, both within and around the lesions, and can have beneficial and detrimental effects on MS pathogenesis. A possible mechanism for the neuroprotective effect in MS involves the release of brain-derived neurotrophic factor (BDNF) by immune cells in peripheral blood and inflammatory lesions, as well as by microglia and astrocytes within the CNS. BDNF is a neurotrophic factor that plays a key role in neuroplasticity and neuronal survival. This review aims to analyze the current understanding of the role that inflammation plays in MS, including the factors that contribute to both beneficial and detrimental effects. Additionally, it explores the potential role of BDNF in MS, as it may modulate neuroinflammation and provide neuroprotection. By obtaining a deeper understanding of the intricate relationship between inflammation and BDNF, new therapeutic strategies for MS may be developed.

Background and aimsHemiplegic migraine (HM) is a rare form of migraine characterized by the presence of a motor and other types of aura. HM can be sporadic or familial. Familial hemiplegic migraine (FHM) is an autosomal dominant disorder, classified into 3 subtypes, based on the gene involved (CACNA1A in FHM1, ATP1A2 in FHM2 and SCN1A in FHM3). The clinical presentation is highly heterogeneous and some attacks may be severe.We report the clinical characteristics and genetic analysis of 12 patients belonging to a family with CACNA1A-p.Thr501Met gene mutation.MethodsWe screened for mutations in CACNA1A gene 15 patients belonging to the same family. The exonic sequences of CACNA1A were analyzed using a Tru-seq® Custom Amplicon (TSCA) (Illumina Inc., San Diego, CA) targeted capture and paired end library kit. Sanger sequencing was used to confirm CACNA1A variants and segregation analysis.ResultsCACNA1A-p.Thr501Met mutation was found in 12 of the 15 patients screened, which was compatible with the diagnosis of FHM1.Attacks of hemiplegic migraine were reported by 10 of the 12 subjects (83.33%). Only one subject developed persistent mild cerebellar symptoms and none of the subjects developed cerebellar atrophy.DiscussionThe variant p.Thr501Met was described previously in association with episodic ataxia and rarely with FHM related to cerebellar symptoms. FHM1 has a broad clinical spectrum and about half of the families have cerebellar involvement. In our study, only one patient developed persistent cerebellar deficits.These data suggest that CACNA1A-p.Thr501Met mutation can occur prevalently as hemiplegic migraine.

The outbreak of a severe acute respiratory syndrome caused by a novel coronavirus (COVID-19), has raised health concerns for patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), who are frequently on long-term immunotherapies. Treatment with IVIg does not increase the risk of contracting COVID-19, and the IVIg administration may have a protective role. However, infusions can expose patients to an increased risk of contracting SARS-CoV-2 due to repeated access to Health Facilities. In this report we analyzed the short-term follow-up of CIDP patients who modified their chronic IVIg therapy during pandemic. About half of CIDP patients regularly treated with IVIg tried to stop treatment and about 10% shifted to SCIg. Forty-two percent of the patients who stopped the treatment reported a clinical deterioration after suspension and had to restart IVIg. This study demonstrated that in selected cases it is possible to successfully stop the chronic IVIg treatment, even in patients who have been treated for several years.

ObjectivesTo investigate the safety and tolerability of COVID-19 vaccines in people with epilepsy (PwE).MethodsIn this multicentric observational cohort study, we recruited adult patients (age > 18 years old) with epilepsy who attended the Outpatient Epilepsy Clinic from 1st July to 30th October 2021. We administered to the patients a structured questionnaire and interview on demographic and epilepsy characteristics, current treatment, previous SARS-CoV-2 infection, vaccine characteristics, post-vaccine seizure relapse, other side effect, variation of sleep habits, caffeine, or alcohol intake. Seizure frequency worsening was defined as a ratio between mean monthly frequency post-vaccination and mean monthly frequency pre-vaccination superior to 1. Patients were categorized in two groups: patients with seizure frequency worsening (WORSE) and patients with seizure stability (STABLE).ResultsA total of 358 people participated with a mean age of 47.46 ± 19.04. Focal seizure (79.1%), generalized epilepsy (20.4%), and unknown types of epilepsy (0.5%) were detected among participants. In total, 31 (8.7%) people expressed that they were not willing to receive a COVID-19 vaccine; 302 patients (92.35%) did not experience an increase in the seizure frequency (STABLE-group) whereas 25 patients (7.65%) had a seizure worsening (WORSE-group). Post-vaccine seizures occurred mainly in the 7 days following the administration of the vaccine. Patients in the WORSE-group were treated with a mean higher number of anti-seizure medication (ASMs) (p = 0.003) and had a higher pre-vaccine seizure frequency (p = 0.009) compared with patients in the STABLE-group. Drug-resistant epilepsy was also associated with seizure worsening (p = 0.01). One-year pre-vaccination seizure frequency pattern demonstrated that patients in the WORSE-group had a higher frequency pattern (p < 0.001). Multivariate analysis of the vaccinated group showed that only the seizure frequency pattern (confidence interval [CI] = 1.257–2.028; p < 0.001) was significantly associated with seizure worsening.ConclusionIn our cohort of vaccinated PwE, only a little percentage had a transient short-term increase of seizure frequency. The present study demonstrates that COVID-19 vaccines have a good safety and tolerability profile in the short term in PwE.

Background: Ventriculoperitoneal shunting (VPS) is the mainstay of treatment for most forms of hydrocephalus; VPS infection (VPSI) is a leading cause of shunt-related morbidity and mortality. A meta-analysis of the existing literature on risk factors for VPSI is currently lacking. Herein, the authors performed a systematic review and meta-analysis to evaluate the role of different clinical factors in the development of VPSI. Methods: A systematic search in the PubMed, Scopus, and Cochrane databases was performed to identify studies comparing patients developing VPSI to controls. The following data were extracted where available: number of patients who developed VPSI vs. number of patients with a regular course, demographics (gender, age at VPS insertion, age > 18 years), average length of hospital stay before shunt implant (days), aetiology of hydrocephalus (tumour-associated hydrocephalus; post-haemorrhagic hydrocephalus; congenital hydrocephalus; spinal dysraphism-associated hydrocephalus; post-infectious hydrocephalus; post-traumatic hydrocephalus; post-craniotomy hydrocephalus), and hydrocephalus type (obstructive hydrocephalus, communicating hydrocephalus, normal-pressure hydrocephalus—NPH). Results: Five studies including 2333 patients (225 with VPS infection) were analysed. Tumour-related hydrocephalus was linked to a lower infection risk (OR 0.418; p < 0.001), while congenital hydrocephalus (OR 2.502; p < 0.001) and spinal dysraphism (OR 2.359; p < 0.001) increased the risk. Conclusions: VPSI represents a serious complication after shunt surgery. Our meta-analysis identifies three key factors influencing the risk of VPSI. VPS-centred, large multicentre prospective studies are needed to possibly confirm the role of the factors we identified and to identify additional ones, enabling earlier detection of VPSI and allowing for better patient care.

Introduction Real-world studies have explored potential predictors of response to anti-calcitonin gene related peptide (CGRP) monoclonal antibodies (mAbs), though results have remained inconsistent. Machine learning (ML) algorithms are becoming increasingly relevant in migraine research, offering a data-driven approach to identifying predictors of response to preventive treatments. To maximize their potential, a clinically applicable and user-oriented framework is needed to promote the use of these algorithms in research and, eventually, as supportive tools in clinical practice. Methods This prospective cohort study included adults with migraine treated with anti-CGRP mAbs (anti-ligand and receptor) at two headache centers. Responders were defined as patients achieving ≥ 50% reduction in monthly headache days (MHDs) at 12 months. A logistic regression model was trained (80%) and tested (20%) using 11 baseline variables, including age, sex, migraine subtype, medication overuse, MHDs, and disability scores. Model performance was evaluated using accuracy, precision, recall, and F1-score. A nomogram was created for future research and clinical application. The model was then validated against an external test cohort treated with anti-CGRP mAbs. Results Among 429 patients, 310 completed twelve months of treatment, with 236 (55.0%) classified as responders. The external test set included 109 patients. The ML model achieved an overall average weighted F1-score of 70.5% between the two test sets, with good performance in identifying “responders” (precision: 0.75, recall: 0.84, F1-score: 0.79). The model yielded predictions with an overall accuracy of 74% when tested against an external test cohort. Chronic migraine status, older age, and lower baseline MHDs were associated with higher response likelihood. Medication overuse and frequent analgesic use were negatively associated with response. The nomogram provided a clinically interpretable tool to estimate response probability, providing a total score named “CGRP Score” ( C GRP mAbs G lobal R esponse P rediction). Conclusion This ML-based predictive score achieved a good performance in identifying responders to anti-CGRP mAbs. The nomogram has the potential to be a practical, user-friendly tool for supporting clinical decision-making after validation.

This study assessed whether continued treatment with anti‐CGRP monoclonal antibodies (mAbs) is driven more by reductions in monthly migraine days (MMDs) or patients' global impression of change (PGIC), a patient‐reported outcome. Among 169 patients treated with anti‐CGRP mAbs, 21.3% discontinued due to ineffectiveness. PGIC responders (≥ 5) at month 12 were 69.8%, whereas MMD responders (≥ 50% reduction) were 59.2%. Both were significantly associated with discontinuation (PGIC: χ2 = 33.474, φ = 0.445; MMD: χ2 = 29.884, φ = 0.421; p < 0.0001). PGIC showed a stronger correlation with discontinuation (rpb = 0.541) than MMD reduction (rpb = 0.470). These findings highlight PGIC as strongly associated with treatment response, supporting the need for PROMs in evaluating migraine treatment effectiveness.

Objective Soluble CD27 is a promising cerebrospinal fluid inflammatory biomarker in multiple sclerosis. In this study, we investigate relevant immune and neuro-pathological features of soluble CD27 in multiple sclerosis. Methods Protein levels of soluble CD27 were correlated to inflammatory cell subpopulations and inflammatory cytokines and chemokines detected in cerebrospinal fluid of 137 patients with multiple sclerosis and 47 patients with inflammatory and non-inflammatory neurological disease from three independent cohorts. Production of soluble CD27 was investigated in cell cultures of activated T and B cells and CD27-knockout T cells. In a study including matched cerebrospinal fluid and post-mortem brain tissues of patients with multiple sclerosis and control cases, levels of soluble CD27 were correlated with perivascular and meningeal infiltrates and with neuropathological features. Results We demonstrate that soluble CD27 favours the differentiation of interferon-γ-producing T cells and is released through a secretory mechanism activated by TCR engagement and regulated by neutral sphingomyelinase. We also show that the levels of soluble CD27 correlate with the representation of inflammatory T cell subsets in the CSF of patients with relapsing-remitting multiple sclerosis and with the magnitude of perivascular and meningeal CD27 + CD4 + and CD8 + T cell infiltrates in post-mortem central nervous system tissue, defining a subgroup of patients with extensive active inflammatory lesions. Interpretation Our results demonstrate that soluble CD27 is a biomarker of disease activity, potentially informative for personalized treatment and monitoring of treatment outcomes.