Seizure risk in multiple sclerosis patients treated with disease-modifying therapy: A systematic review and network meta-analysis

Incidence and determinants of seizures in multiple sclerosis: a meta-analysis of randomised clinical trials

BACKGROUND

Seizures are reported to be more prevalent in individuals with multiple sclerosis (MS) compared with the general population. Existing data predominantly originate from population-based studies, which introduce variability in methodologies and are vulnerable to selection and reporting biases.

METHODS

This meta-analysis aims to assess the incidence of seizures in patients participating in randomised clinical trials and to identify potential contributing factors. Data were extracted from 60 articles published from 1993 to 2022. The pooled effect size, representing the incidence rate of seizure events, was estimated using a random-effect model. Metaregression was employed to explore factors influencing the pooled effect size.

RESULTS

The meta-analysis included data from 53 535 patients and 120 seizure events in a median follow-up of 2 years. The pooled incidence rate of seizures was 68.0 per 100 000 patient-years, significantly higher than the general population rate of 34.6. Generalised tonic-clonic seizures were the most common type reported, although there was a high risk of misclassification for focal seizures with secondary generalisation. Disease progression, longer disease duration, higher disability levels and lower brain volume were associated with a higher incidence of seizures. Particularly, sphingosine-1-phosphate receptor (S1PR) modulators exhibited a 2.45-fold increased risk of seizures compared with placebo or comparators, with a risk difference of 20.5 events per 100 000 patient-years.

CONCLUSIONS

Patients with MS face a nearly twofold higher seizure risk compared with the general population. This risk appears to be associated not only with disease burden but also with S1PR modulators. Our findings underscore epilepsy as a significant comorbidity in MS and emphasise the necessity for further research into its triggers, preventive measures and treatment strategies.

Improving the classification of multiple sclerosis and cerebral small vessel disease with interpretable transfer attention neural network

As an autoimmune-mediated inflammatory demyelinating disease of the central nervous system, multiple sclerosis (MS) is often confused with cerebral small vessel disease (cSVD), which is a regional pathological change in brain tissue with unknown pathogenesis. This is due to their similar clinical presentations and imaging manifestations. That misdiagnosis can significantly increase the occurrence of adverse events. Delayed or incorrect treatment is one of the most important causes of MS progression. Therefore, the development of a practical diagnostic imaging aid could significantly reduce the risk of misdiagnosis and improve patient prognosis. We propose an interpretable deep learning (DL) model that differentiates MS and cSVD using T2-weighted fluid-attenuated inversion recovery (FLAIR) images. Transfer learning (TL) was utilized to extract features from the ImageNet dataset. This pioneering model marks the first of its kind in neuroimaging, showing great potential in enhancing differential diagnostic capabilities within the field of neurological disorders. Our model extracts the texture features of the images and achieves more robust feature learning through two attention modules. The attention maps provided by the attention modules provide model interpretation to validate model learning and reveal more information to physicians. Finally, the proposed model is trained end-to-end using focal loss to reduce the influence of class imbalance. The model was validated using clinically diagnosed MS (n=112) and cSVD (n=321) patients from the Beijing Tiantan Hospital. The performance of the proposed model was better than that of two commonly used DL approaches, with a mean balanced accuracy of 86.06 % and a mean area under the receiver operating characteristic curve of 98.78 %. Moreover, the generated attention heat maps showed that the proposed model could focus on the lesion signatures in the image. The proposed model provides a practical diagnostic imaging aid for the use of routinely available imaging techniques such as magnetic resonance imaging to classify MS and cSVD by linking DL to human brain disease. We anticipate a substantial improvement in accurately distinguishing between various neurological conditions through this novel model.

Clinical characteristics, course and prognosis of Multiple Sclerosis patients with epilepsy. A case control study: MS and epilepsy

BACKGROUND AND PURPOSE

Although more common than in the general population, seizures are an atypical manifestation of multiple sclerosis (MS) and their pathophysiology is not well understood. This study aims to examine the prevalence, clinical characteristics, brain imaging findings and course of epilepsy, presenting in patients with MS.

METHODS

Observational retrospective study of MS patients evaluated at a single MS reference center in Buenos Aires, Argentina, between 2011 and 2022, focusing on those who developed epilepsy (EMS). Clinical, demographic, and prognostic factors were evaluated and compared to a control group of non-epileptic MS patients (NEMS). To analyze specific epilepsy characteristics, a second control group of patients with non-lesional focal epilepsy (FNLE) was also included.

RESULTS

Twenty-five patients (18 women), were diagnosed with epilepsy, corresponding to a prevalence of 1.95%. Comparison of brain imaging characteristics between EMS and NEMS patients showed brain atrophy (32% vs 6.1%, p<0.01), as well as cortical (26% vs 4%, p=0.03) and juxtacortical lesions (84% vs 55%, p=0.05), were more frequent in EMS patients. However, after multivariate analysis, cortical atrophy was the only variable linked to a significant increase in risk of epilepsy (OR 24, 95%CI=2.3-200, p<0.01). No significant differences in clinical characteristics, disease activity, disability levels, response to disease modified treatment (DMT) or lack of DMT efficacy were observed between MS patients with or without epilepsy. Most patients received anti-seizure medication (ASM), and seizure control was better in EMS than in FNLE patients (92% vs 58%, p=0.022) with no differences found in drug resistance. We did not find predictors of seizure recurrence in the population studied.

CONCLUSION

We observed a lower prevalence of epilepsy in this group of MS patients, compared to other reported cohorts. Although epilepsy seems to have a benign course in MS patients, cortical atrophy appears to be an important contributor to the development of secondary epilepsy in MS patients. Further investigations will be necessary to identify risk factors or biomarkers predicting increased epilepsy risk in MS.

Rat Ovarian Function Is Impaired during Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is an autoimmune disease affecting the CNS and occurring far more prevalently in women than in men. In both MS and its animal models, sex hormones play important immunomodulatory roles. We have previously shown that experimental autoimmune encephalomyelitis (EAE) affects the hypothalamic-pituitary-gonadal axis in rats of both sexes and induces an arrest in the estrous cycle in females. To investigate the gonadal status in female rats with EAE, we explored ovarian morphometric parameters, circulating and intraovarian sex steroid levels, and the expression of steroidogenic machinery components in the ovarian tissue. A prolonged state of diestrus was recorded during the peak of EAE, with maintenance of the corpora lutea, elevated intraovarian progesterone levels, and increased gene and protein expression of StAR, similar to the state of pseudopregnancy. The decrease in CYP17A1 protein expression was followed by a decrease in ovarian testosterone and estradiol levels. On the contrary, serum testosterone levels were slightly increased. With unchanged serum estradiol levels, these results point at extra-gonadal sites of sex steroid biosynthesis and catabolism as important regulators of their circulating levels. Our study suggests alterations in the function of the female reproductive system during central autoimmunity and highlights the bidirectional relationships between hormonal status and EAE.