Serum biomarker levels predict disability progression in patients with primary progressive multiple sclerosis

医学 扩大残疾状况量表 生物标志物 多发性硬化 内科学 队列 肿瘤科 胃肠病学 免疫学 生物化学 化学
作者
Nicolás Fissolo,Pascal Benkert,Jaume Sastre‐Garriga,Neus Mongay‐Ochoa,Andreu Vilaseca-Jolonch,Sara Llufriú,Yolanda Blanco,Harald Hegen,Klaus Berek,Francisco Pérez‐Miralles,Konrad Rejdak,Luisa María Villar,Enric Monreal,Roberto Álvarez‐Lafuente,O. Soylu,Ahmed Abdelhak,Franziska Bachhuber,Hayrettin Tumani,Sergio Martínez‐Yélamos,Antonio Sánchez,Antonio Garcı́a-Merino,Lucía Gutiérrez,Tamara Castillo‐Triviño,Jan Lycke,Igal Rosenstein,Roberto Furlan,Massimo Filippi,Nieves Téllez,Lluı́s Ramió-Torrentà,Jan D. Lünemann,Heinz Wiendl,Sara Eichau,Michael Khalil,Jens Kühle,Xavier Montalbán,Manuel Comabella
出处
期刊:Journal of Neurology, Neurosurgery, and Psychiatry [BMJ]
卷期号:: jnnp-332251 被引量:4
标识
DOI:10.1136/jnnp-2023-332251
摘要

Background We 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). Methods A 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. Results Median (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. Conclusions Levels 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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