Humoral and T-cell response to SARS-CoV-2 mRNA vaccine in multiple sclerosis patients: Correlations with DMTs and clinical variables.

Disease-modifying therapies (DMTs) can affect vaccine responses in individuals with multiple sclerosis (MS). We assessed the humoral and T-cell responses following SARS-CoV-2 mRNA vaccination in MS patients receiving various DMTs. We prospectively enrolled 243 participants, including 113 healthy control subjects and 130 MS patients. Blood samples for detecting SARS-CoV-2 antibodies were collected at three time points: T0, before the first vaccine dose; T1, before the second dose; and T2, one month after the second dose. In a subgroup of 51 patients and 20 controls, samples were collected at T0 and T2 to assess the T-cell immune response to the Spike antigen of SARS-CoV-2 using ELISPOT-IFNγ. The IgG levels in patients treated with fingolimod and ocrelizumab (159.1 AU/ml and 467.1 AU/ml, respectively) were significantly lower than those in healthy controls and patients on other DMTs (P â€‹< â€‹0.0001). The mean Ig titers were higher in patients with an absolute lymphocyte count ≥1000 â€‹cells/mm3 compared to those with a count between 500 and 1000 and with a count <500 (mean â€‹± â€‹SD:7205.6 â€‹± â€‹7339.2, 2413.1 â€‹± â€‹4515.4 and 165.9 â€‹± â€‹152.2, respectively; p â€‹= â€‹0.008). We found correlations between antibody levels and age (r â€‹= â€‹0.233, p â€‹= â€‹0.008). A positive Spike-specific T-cell response was detectable in 100 â€‹% of vaccinated healthy controls and patients treated with teriflunomide, dimethyl-fumarate, and natalizumab, in 90.5 â€‹% of fingolimod patients, and in 63.8 â€‹% of ocrelizumab patients. There is a correlation between IgG-specific titer after SARS-CoV-2 vaccination and clinical variables (age, lymphocyte count). Notably, a T-cell-specific response to SARS-CoV-2 developed in patients treated with fingolimod and ocrelizumab, even with lower rates of humoral response.

Data-driven clustering of combined Functional Motor Disorders based on the Italian registry.

Introduction: Functional Motor Disorders (FMDs) represent nosological entities with no clear phenotypic characterization, especially in patients with multiple (combined FMDs) motor manifestations. A data-driven approach using cluster analysis of clinical data has been proposed as an analytic method to obtain non-hierarchical unbiased classifications. The study aimed to identify clinical subtypes of combined FMDs using a data-driven approach to overcome possible limits related to "a priori" classifications and clinical overlapping. Methods: Data were obtained by the Italian Registry of Functional Motor Disorders. Patients identified with multiple or "combined" FMDs by standardized clinical assessments were selected to be analyzed. Non-hierarchical cluster analysis was performed based on FMDs phenomenology. Multivariate analysis was then performed after adjustment for principal confounding variables. Results: From a study population of n = 410 subjects with FMDs, we selected n = 188 subjects [women: 133 (70.7%); age: 47.9 ± 14.4 years; disease duration: 6.4 ± 7.7 years] presenting combined FMDs to be analyzed. Based on motor phenotype, two independent clusters were identified: Cluster C1 (n = 82; 43.6%) and Cluster C2 (n = 106; 56.4%). Cluster C1 was characterized by functional tremor plus parkinsonism as the main clinical phenotype. Cluster C2 mainly included subjects with functional weakness. Cluster C1 included older subjects suffering from anxiety who were more treated with botulinum toxin and antiepileptics. Cluster C2 included younger subjects referring to different associated symptoms, such as pain, headache, and visual disturbances, who were more treated with antidepressants. Conclusion: Using a data-driven approach of clinical data from the Italian registry, we differentiated clinical subtypes among combined FMDs to be validated by prospective studies.