Background:
Few data are available on very long-term follow-up of pediatric multiple sclerosis (MS) patients treated with disease modifying treatments (DMTs).
Objectives:
To present a long-term ...follow-up of a cohort of Pediatric-MS patients starting injectable first-line agents.
Methods:
Data regarding treatments, annualized relapse rate (ARR), Expanded Disability Status Scale (EDSS) score, and serious adverse event were collected. Baseline characteristics were tested in multivariate analysis to identify predictors of disease evolution.
Results:
In total, 97 patients were followed for 12.5 ± 3.3 years. They started therapy at 13.9 ± 2.1 years, 88 with interferons and 9 with copaxone. During the whole follow-up, 82 patients changed therapy, switching to immunosuppressors/second-line treatment in 58% of cases. Compared to pre-treatment phase, the ARR was significantly reduced during the first treatment (from 3.2 ± 2.6 to 0.7 ± 1.5, p < 0.001), and it remained low during the whole follow-up (0.3 ± 0.2, p < 0.001). At last observation, 40% had disability worsening, but EDSS score remained <4 in 89%. One patient died at age of 23 years due to MS. One case of natalizumab-related progressive multifocal encephalopathy (PML) was recorded. Starting therapy before 12 years of age resulted in a better course of disease in multivariate analysis.
Conclusion:
Pediatric-MS patients benefited from interferons/copaxone, but the majority had to switch to more powerful drugs. Starting therapy before 12 years of age could lead to a more favorable outcome.
Background:
Development of long-lasting anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) T-cell responses in persons with multiple sclerosis (pwMS) treated with ocrelizumab is ...questioned.
Objective:
Investigate antiviral T-cell responses after infection with SARS-CoV-2 in ocrelizumab-treated pwMS. Control groups included ocrelizumab-treated pwMS without SARS-CoV-2 infection, and non-MS individuals with and without SARS-CoV-2 infection.
Methods:
Peripheral blood mononuclear cells were stimulated with SARS-CoV-2 peptide pools and T-cell reactivity was assessed by ELISPOT for interferon (IFN)-γ detection, and by multiparametric fluorescence-activated cell sorting (FACS) analyses for assessment and characterization of T-cell activation.
Results:
ELISPOT assay against the spike and the N protein of SARS-CoV-2 displayed specific T-cell reactivity in 28/29 (96%) pwMS treated with ocrelizumab and infected by SARS-CoV-2, similar to infected persons without MS. This reactivity was present 1 year after infection and independent from the time of ocrelizumab infusion. FACS analysis following stimulation with SARS-CoV-2 peptide pools showed the presence of activation-induced markers (AIMs) in both CD4+ and CD8+ T-cell subsets in 96% and 92% of these individuals, respectively. Within naïve AIM+ CD4+ and CD8+ T-cells, we detected T memory stem cells, suggesting the acquisition of long-term memory.
Conclusions:
B-cell depletion using ocrelizumab does not impair the development of long-lasting anti-SARS-CoV-2 T-cell responses.
Objectives:
To assess the impact of timing of natalizumab cessation/redosing on long-term maternal and infant outcomes in 72 out of the original 74 pregnancies of the Italian Pregnancy Dataset in ...multiple sclerosis (MS).
Methods:
Maternal outcomes in patients who received natalizumab until conception and restarted the drug within 1 month after delivery (“treatment approach,” (TA)) and patients who stopped natalizumab before conception and/or restarted the drug later than 1 month after delivery (“conservative approach,” (CA)) were compared through multivariable Cox regression analyses. Pediatric outcomes were assessed through a semi-structured questionnaire.
Results:
After a mean follow-up of 6.1 years, CA (hazard ratio (HR) = 4.1, 95% CI 1.6–10.6, p = 0.003) was the only predictor of relapse occurrence. Worsening on the Expanded Disability Status Scale (EDSS) was associated with higher annualized relapse-rate during the follow-up (HR = 3.3, 95% CI 1.4–7.9 p = 0.007). We found no major development abnormalities in children.
Discussion:
Our data confirm that TA reduces the risk of disease activity; we did not observe an increase in major development abnormalities in the child.
JC virus (JCV) is an opportunistic virus known to cause progressive multifocal leukoencephalopathy. Anti-JC virus (Anti-JCV) antibody prevalence in a large, geographically diverse, multi-national ...multiple sclerosis (MS) cohort was compared in a cross-sectional study. Overall, anti-JCV antibody prevalence was 57.6%. Anti-JCV antibody prevalence in MS patients ranged from approximately 47% to 68% across these countries: Norway, 47.4%; Denmark, 52.6%; Israel, 56.6%; France, 57.6%; Italy, 58.3%; Sweden, 59.0%; Germany, 59.1%; Austria, 66.7% and Turkey, 67.7%. Prevalence increased with age (from 49.5% in patients < 30 years of age to 66.5% in patients ≥ 60 years of age; p < 0.0001 comparing all age categories), was lower in females than in males (55.8% versus 61.9%; p < 0.0001) and was not affected by prior immunosuppressant or natalizumab use.
► Expression of 1145 miRNAs was measured in PBMCs of 19 MS patients and 14 controls. ► Whole genome mRNA profiling was performed on the same population. ► 104 miRNAs have been identified as ...deregulated in MS patients. ► Let-7g and miR-150 have been validated in a replication sample. ► Novel putative deregulated miRNA and mRNA transcripts have been identified.
Identification of novel targets and biomarkers, such as microRNAs, is extremely helpful to understand the pathogenetic mechanisms in a disease like multiple sclerosis (MS). We tested the expression profile of 1145 microRNAs in peripheral blood mononuclear cells (PBMCs) of 19 MS patients and 14 controls, and we further explored their function by performing a whole-genome mRNA profiling in same subjects and using bioinformatic prediction tool. A total of 104 miRNAs have been identified as deregulated in MS patients; 2/10 which ranked highest (let-7g and miR-150) have been validated in a replication sample, leading to the identification of putative target genes.
Background: Systemic lupus erythematosus (SLE) is associated with a constellation of complications affecting multiple organs, including neuropsychiatric manifestations (NPSLE) and ischaemic events, ...leading to increased long-term morbidity. Antiphospholipid antibodies (aPL) are a major determinant of vascular inflammation and thromboembolic risk. The diagnostic role of anti-phosphatidylserine/prothrombin (aPS/PT) antibodies in this setting is incompletely defined.
Aim: To verify whether aPS/PT add to diagnostics and disease stratification in patients with SLE with or without other aPL.
Methods: 131 consecutive patients were studied, including 20 patients with SLE and secondary antiphospholipid syndrome (APS). aPS/PT IgG and IgM were assessed through ELISA and patients were stratified based on the presence of other aPL, on their clinical and laboratory features at time of blood sampling and on their clinical history. Synthetic indices of disease activity, chronic damage and cardiovascular risk were calculated at time of venipuncture.
Results: Fifty-one (38.9%) patients with SLE had aPS/PT and 15 (11.5%) patients had aPS/PT as the only aPL (aPS/PT-only). aPS/PT-only patients had a significantly higher prevalence of NPSLE than quadruple aPL-negative patients (p = .007). Patients with aPS/PT were more likely to have a history of ischaemia, thrombocytopenia and Libman-Sacks' endocarditis. The presence of aPS/PT also associated with previous accrual of at least one damage item (p = .043), but had limited predictive values for damage progression in the short term.
Conclusion: aPS/PT antibodies provide non-redundant information that could contribute to risk assessment and stratification of patients with SLE.
A personalized approach is strongly advocated for treatment selection in Multiple Sclerosis patients due to the high number of available drugs. Machine learning methods proved to be valuable tools in ...the context of precision medicine. In the present work, we applied machine learning methods to identify a combined clinical and genetic signature of response to fingolimod that could support the prediction of drug response. Two cohorts of fingolimod-treated patients from Italy and France were enrolled and divided into training, validation, and test set. Random forest training and robust feature selection were performed in the first two sets respectively, and the independent test set was used to evaluate model performance. A genetic-only model and a combined clinical-genetic model were obtained. Overall, 381 patients were classified according to the NEDA-3 criterion at 2 years; we identified a genetic model, including 123 SNPs, that was able to predict fingolimod response with an AUROC= 0.65 in the independent test set. When combining clinical data, the model accuracy increased to an AUROC= 0.71. Integrating clinical and genetic data by means of machine learning methods can help in the prediction of response to fingolimod, even though further studies are required to definitely extend this approach to clinical applications.
Few studies have systematically addressed the role of epidural analgesia and caesarean delivery in predicting the post-partum disease activity in women with Multiple Sclerosis (MS).The objective of ...this study was to assess the impact of epidural analgesia (EA) and caesarean delivery (CD) on the risk of post-partum relapses and disability in women with MS.
In the context of an Italian prospective study on the safety of immunomodulators in pregnancy, we included pregnancies occurred between 2002 and 2008 in women with MS regularly followed-up in 21 Italian MS centers. Data were gathered through a standardized, semi-structured interview, dealing with pregnancy outcomes, breastfeeding, type of delivery (vaginal or caesarean) and EA. The risk of post-partum relapses and disability progression (1 point on the Expanded Disability Status Sclae, EDSS, point, confirmed after six months) was assessed through a logistic multivariate regression analysis.
We collected data on 423 pregnancies in 415 women. Among these, 349 pregnancies resulted in full term deliveries, with a post-partum follow-up of at least one year (mean follow-up period 5.5±3.1 years). One hundred and fifty-five patients (44.4%) underwent CD and 65 (18.5%) EA. In the multivariate analysis neither CD, nor EA were associated with a higher risk of post-partum relapses. Post-partum relapses were related to a higher EDSS score at conception (OR=1.42; 95% CI 1.11-1.82; p=0.005), a higher number of relapses in the year before pregnancy (OR=1.62; 95% CI 1.15-2.29; p=0.006) and during pregnancy (OR=3.07; 95% CI 1.40-6.72; p=0.005). Likewise, CD and EA were not associated with disability progression on the EDSS after delivery. The only significant predictor of disability progression was the occurrence of relapses in the year after delivery (disability progression in the year after delivery: OR= 4.00; 95% CI 2.0-8.2; p<0.001; disability progression over the whole follow-up period: OR= 2.0; 95% CI 1.2-3.3; p=0.005).
Our findings, show no correlation between EA, CD and postpartum relapses and disability. Therefore these procedures can safely be applied in MS patients. On the other hand, post-partum relapses are significantly associated with increased disability, which calls for the need of preventive therapies after delivery.
Peripheral blood mononuclear cells (PBMCs) bear specific dysregulations in genes and pathways at distinct stages of multiple sclerosis (MS) that may help with classifying MS and non-MS subjects, ...specifying the early stage of disease, or discriminating among MS courses. Here we describe an unbiased machine learning workflow to build MS stage-specific classifiers based on PBMC transcriptomics profiles from more than 300 individuals, including healthy subjects and patients with clinically isolated syndromes, relapsing-remitting MS, primary or secondary progressive MS, or other neurological disorders. The pipeline, designed to optimize and compare the performance of distinct machine learning algorithms in the training cohort, generates predictive models not influenced by demographic features, such as age and gender, and displays high accuracy in the independent validation cohort. Proper application of machine learning to transcriptional profiles of circulating blood cells may allow identification of disease state and stage in MS.
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Generated PBMC transcriptomes from multiple sclerosis and control subjectsUnbiased machine learning workflow allows algorithm comparison and optimizationClassifiers built on training cohort have high accuracy in the independent test setPBMC transcriptomes identify disease state and stage in multiple sclerosis
Acquaviva et al. describe the application of machine learning to transcriptional profiles of peripheral immune cells from more than 300 healthy and neurological subjects. Classification models built on the training cohort display high accuracy in the independent test set and identify disease state and stage in multiple sclerosis.
Only few studies have assessed safety of in utero exposure to glatiramer acetate (GA). Following a previous study assessing the safety of interferon beta (IFNB) pregnancy exposure in multiple ...sclerosis (MS), we aimed to assess pregnancy and fetal outcomes after in utero exposure to GA, using the same dataset, with a specific focus on the risk of spontaneous abortion.
We recruited MS patients, prospectively followed-up in 21 Italian MS Centres, for whom a pregnancy was recorded in the period 2002-2008. Patients were divided into 2 groups: drug-exposed pregnancies (EP: suspension of the drug less than 4 weeks from conception); non-exposed pregnancies (NEP: suspension of the drug at least 4 weeks from conception or never treated pregnancies). All the patients were administered a structured interview which gathered detailed information on pregnancy course and outcomes, as well as on possible confounders. Multivariate logistic and linear models were used for treatment comparisons.
Data on 423 pregnancies were collected, 17 were classified as EP to GA, 88 as EP to IFNB, 318 as NEP. Pregnancies resulted in 16 live births in the GA EP, 75 live births in the IFNB EP, 295 live births in the NEP. GA exposure was not significantly associated with an increased risk of spontaneous abortion (OR = 0.44;95% CI 0.044-4.51;p = 0.49). Mean birth weight and length were not significantly different in pregnancies exposed to GA than in non exposed pregnancies (p = 0.751). The frequency of preterm delivery, observed in 4 subjects exposed to GA (25% of full term deliveries), was not significantly higher in pregnancies exposed to GA than in those non exposed (p > 0.735). These findings were confirmed in the multivariate analysis. There were neither major complications nor malformations after GA exposure.
Data in our cohort show that mother's GA exposure is not associated with a higher frequency of spontaneous abortion, neither other negative pregnancy and fetal outcomes. Our findings point to the safety of in utero GA exposure and can support neurologists in the therapeutic counselling of MS women planning a pregnancy.
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