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- Fissolo, N., et al.
(author)
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Serum biomarker levels predict disability progression in patients with primary progressive multiple sclerosis
- 2024
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In: Journal of Neurology Neurosurgery and Psychiatry. - 0022-3050. ; 95:5, s. 410-418
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Journal article (peer-reviewed)abstract
- BackgroundWe aimed to investigate the potential of serum biomarker levels to predict disability progression in a multicentric real-world cohort of patients with primary progressive multiple sclerosis (PPMS).MethodsA total of 141 patients with PPMS from 18 European MS centres were included. Disability progression was investigated using change in Expanded Disability Status Scale (EDSS) score over three time intervals: baseline to 2 years, 6 years and to the last follow-up. Serum levels of neurofilament light chain (sNfL), glial fibrillar acidic protein (sGFAP) and chitinase 3-like 1 (sCHI3L1) were measured using single-molecule array assays at baseline. Correlations between biomarker levels, and between biomarkers and age were quantified using Spearman's r. Univariable and multivariable linear models were performed to assess associations between biomarker levels and EDSS change over the different time periods.ResultsMedian (IQR) age of patients was 52.9 (46.4-58.5) years, and 58 (41.1%) were men. Median follow-up time was 9.1 (7.0-12.6) years. Only 8 (5.7%) patients received treatment during follow-up. sNfL and sGFAP levels were moderately correlated (r=0.43) and both weakly correlated with sCHI3L1 levels (r=0.19 and r=0.17, respectively). In multivariable analyses, levels of the three biomarkers were associated with EDSS changes across all time periods. However, when analysis was restricted to non-inflammatory patients according to clinical and radiological parameters (n=64), only sCHI3L1 levels remained associated with future EDSS change.ConclusionsLevels of sNfL, sGFAP and sCHI3L1 are prognostic biomarkers associated with disability progression in patients with PPMS, being CHI3L1 findings less dependent on the inflammatory component associated with disease progression.
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- Wilson, D., et al.
(author)
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Development and multi-center validation of a fully automated digital immunoassay for neurofilament light chain: toward a clinical blood test for neuronal injury
- 2024
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In: Clinical Chemistry and Laboratory Medicine. - 1434-6621 .- 1437-4331. ; 62:2, s. 322-331
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Journal article (peer-reviewed)abstract
- Objectives Neurofilament light chain (NfL) has emerged as a promising biomarker for detecting and monitoring axonal injury. Until recently, NfL could only be reliably measured in cerebrospinal fluid, but digital single molecule array (Simoa) technology has enabled its precise measurement in blood samples where it is typically 50-100 times less abundant. We report development and multi-center validation of a novel fully automated digital immunoassay for NfL in serum for informing axonal injury status.Methods A 45-min immunoassay for serum NfL was developed for use on an automated digital analyzer based on Simoa technology. The analytical performance (sensitivity, precision, reproducibility, linearity, sample type) was characterized and then cross validated across 17 laboratories in 10 countries. Analytical performance for clinical NfL measurement was examined in individual patients with relapsing remitting multiple sclerosis (RRMS) after 3 months of disease modifying treatment (DMT) with fingolimod.Results The assay exhibited a lower limit of detection (LLoD) of 0.05 ng/L, a lower limit of quantification (LLoQ) of 0.8 ng/L, and between-laboratory imprecision <10 % across 17 validation sites. All tested samples had measurable NfL concentrations well above the LLoQ. In matched pre-post treatment samples, decreases in NfL were observed in 26/29 RRMS patients three months after DMT start, with significant decreases detected in a majority of patients.Conclusions The sensitivity characteristics and reproducible performance across laboratories combined with full automation make this assay suitable for clinical use for NfL assessment, monitoring in individual patients, and cross-comparisons of results across multiple sites.
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