Clinical, prognostic and pathophysiological implications of MOG-IgG detection in the CSF: the importance of intrathecal MOG-IgG synthesis.

BACKGROUND: Cerebrospinal fluid myelin oligodendrocyte glycoprotein IgG (CSF MOG-IgG) are found in a proportion of patients with MOG antibody-associated disorder (MOGAD) and have been associated with severe disease presentations. However, most studies did not systematically investigate the role of MOG-IgG intrathecal synthesis (ITS). METHODS: We retrospectively studied 960 consecutive patients with paired serum and CSF samples screened for MOG-IgG using a live cell-based assays. MOG-IgG-specific antibody index (AIMOG) was systematically calculated using serum and CSF titres to assess MOG-IgG ITS, and clinical features were compared between MOG-IgG CSF+/CSF- and ITS+/ITS- patients. RESULTS: MOG-IgG were found in 55/960 patients (5.7%; serum+/CSF-: 58.2%, serum+/CSF+: 34.5%; serum-/CSF+: 7.3%). Serum/CSF MOG-IgG titres showed a moderate correlation in patients without ITS (ρ=0.47 (CI 0.18 to 0.68), p<0.001), but not in those with ITS (ρ=0.14 (CI -0.46 to -0.65), p=0.65). There were no clinical-paraclinical differences between MOG-IgG CSF+ vs CSF- patients. Conversely, patients with MOG-IgG ITS showed pyramidal symptoms (73% vs 32%, p=0.03), spinal cord involvement (82% vs 39%, p=0.02) and severe outcome at follow-up (36% vs 5%, p=0.02) more frequently than those without MOG-IgG ITS. A multivariate logistic regression model indicated that MOG-IgG ITS was an independent predictor of a poor outcome (OR: 14.93 (CI 1.40 to 19.1); p=0.03). AIMOG correlated with Expanded Disability Status Scale (EDSS) scores at disease nadir and at last follow-up (p=0.02 and p=0.01). CONCLUSIONS: Consistently with physiopathology, MOG-IgG ITS is a promising prognostic factor in MOGAD, and its calculation could enhance the clinical relevance of CSF MOG-IgG testing, making a case for its introduction in clinical practice.

Early prediction of unfavorable evolution after a first clinical episode suggestive of multiple sclerosis: the EUMUS score.

BACKGROUND: Predicting disease progression in patients with the first clinical episode suggestive of multiple sclerosis (MS) is crucial for personalized therapeutic approaches. This study aimed to develop the EUMUS score for accurately estimating the risk of early evidence of disease activity and progression (EDA). METHODS: Retrospective analysis was conducted on data from 221 patients with a first clinical MS episode collected from four Italian MS centers. Various variables including socio-demographics, clinical features, cerebrospinal fluid analysis, evoked potentials, and brain MRI were considered. A prognostic multivariate regression model was identified to develop the EUMUS score. The optimal cutoff for predicting the transition from no evidence of disease activity (NEDA3) to EDA was determined. The accuracy of the prognostic model and score were tested in a separate UK MS cohort. RESULTS: After 12 months, 61.54% of patients experienced relapses and/or new MRI lesions. Younger age (OR 0.96, CI 0.93-0.99; p = 0.005), MRI infratentorial lesion(s) at baseline (OR 2.21, CI 1.27-3.87; p = 0.005), positive oligoclonal bands (OR 2.89, CI 1.47-5.69; p = 0.002), and abnormal lower limb somatosensory-evoked potentials (OR 2.77, CI 1.41-5.42; p = 0.003) were significantly associated with increased risk of EDA. The EUMUS score demonstrated good specificity (72%) and correctly classified 80% of patients with EDA in the independent UK cohort. CONCLUSIONS: The EUMUS score is a simple and useful tool for predicting MS evolution within 12 months of the first clinical episode. It has the potential to guide personalized therapeutic approaches and aid in clinical decision-making.

MOG-IgG testing strategies in accordance with the 2023 MOGAD criteria: a clinical-laboratory assessment.

BACKGROUND: Live cell-based assay (LCBA) is the gold standard for MOG-IgG detection, and fixed CBA (FCBA) is a widely used commercial alternative. Recent criteria attributed a diagnostic value to MOG-IgG titration with both LCBA and FCBA, with low-titre samples requiring additional supporting features for MOGAD diagnosis. However, FCBA titration is not validated. We aimed to assess the impact of the criteria-based MOG-IgG testing in MOGAD diagnosis. METHODS: Thirty-eight serum samples of LCBA MOG-IgG1-positive MOGAD patients were titred on MOG-IgG LCBA and FCBA, and the presence of supporting features for MOGAD assessed. MOGAD criteria were evaluated in four testing scenarios: (a) FCBA without titration; (b) FCBA with titration; c) LCBA without titration; (d) LCBA with titration. RESULTS: FCBA without titration failed to reach MOGAD diagnosis in 11/38 patients (28.9%, negative results in 5, lack of supporting features in 6). Patients with unconfirmed diagnosis had optic neuritis (ON, n = 8), or transverse myelitis (TM, n = 3). FCBA with titration allowed MOGAD diagnosis in 4 additional patients. Correlation between LCBA and FCBA titres was moderate (Spearman's rho 0.6, p < 0.001). CONCLUSIONS: FCBA yields high rate of misdiagnosis mainly due a lower analytical sensitivity. FCBA titration provides a moderate diagnostic advantage in FCBA positive patients.

Predicted Expenditure for Prescription Drugs for Multiple Sclerosis in the Italian Market Between 2023 and 2028: Results of the Oracle Project.

INTRODUCTION: Multiple sclerosis (MS) is a chronic neurodegenerative disease that leads to impaired cognitive function and accumulation of disability, with significant socioeconomic burden. Serious unmet need in the context of managing MS has given rise to ongoing research efforts, leading to the launch of new drugs planned for the near future, and subsequent concerns about the sustainability of healthcare systems. This study assessed the changes in the Italian MS market and their impact on the expenditures of the Italian National Healthcare Service between 2023 and 2028. METHODS: A horizon-scanning model was developed to estimate annual expenditure from 2023 to 2028. Annual expenditure for MS was calculated by combining the number of patients treated with each product (clinical inputs) and the yearly costs of therapy (economic inputs). Baseline inputs (2020-2022) were collected from IQVIA® real-world data, while input estimation for the 5-year forecast was integrated with analog analyses and the insights of clinicians and former payers. RESULTS: The number of equivalent patients treated in 2028 in Italy was estimated at around 67,000, with an increase of 10% versus 2022. In terms of treatment pattern evolution, first-line treatments are expected to reduce their shares from 47% in 2022 to 27% in 2028, and Bruton tyrosine kinase inhibitors are expected to reach 23% of patient shares. Overall, expenditure for MS is estimated to decrease from €721 million in 2022 to €551 million in 2028, mainly due to losses of exclusivity and renegotiation of drug prices. CONCLUSION: Despite the increase in the number of patients treated for MS and the launch of new molecules that will reach high market penetration, the model confirmed sustainability for the Italian National Healthcare Service.

An open-source zero-gradient cell hardware to improve and accelerate durability testing of PEM fuel cells.

The design of an open zero-gradient hardware is proposed in this work. The hardware is thought for characterizing single Polymer Electrolyte Membrane Fuel Cells (PEMFCs), specifically Membrane Electrode Assemblies (MEAs), with a focus on transport application. The objective of the proposed design is to minimize both operation and degradation heterogeneities over the cell active area in order to evaluate material properties only. It is indeed specifically intended to quantify the PEMFC materials performance without accounting for any interdependency between the layers of the MEA and the cell hardware design (e.g. heating/cooling system and flow field features). This is granted by combining high stoichiometry ratios of the gas reactants and limited pressure drops: they indeed keep uniform operating conditions (concentration in the gas phase, relative humidity, pressure and temperature), as verified by the electrochemical and operational characterization. With such characteristics, accurate information about both the performance and the degradation of the MEA materials can be provided. This tool is powerful for assessing the ranking in terms of performance and durability of different PEMFCs, as well as for application in the field of the materials local diagnostics.