Анализ новаторской флюидовой биомаркирующей панели для раннего прогнозирования прогресса, независимого от рецидивной активности при множественном склерозе.
Обработка статьи · этапы, ошибки и управление
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Schilke Edoardo Dalmato, Frigo Maura, Fusco Maria Letizia, Cappellani Adele, Cereda Diletta, Zoia Chiara Paola, Cavaletti Guido
Аннотация
Оригинал публикации
Analysis of an innovative fluid biomarker panel for early prediction of progression independent of relapse activity in multiple sclerosis.
BACKGROUND: Progression independent of relapse activity (PIRA) may occur in patients with relapsing multiple sclerosis (MS) and is a major contributor to disability accumulation.
OBJECTIVES: We evaluated whether a panel of cerebrospinal fluid (CSF) biomarkers (neurofilament light chain (NfL), glial fibrillary acid protein (GFAP), total-Tau (T-Tau), ubiquitin C-terminal hydrolase 1 (UCHL-1), and the phospho-Tau (P-Tau)181/T-Tau ratio) at diagnosis could discriminate patients who will develop PIRA in early disease phases.
METHODS: CSF levels of NfL, GFAP, T-Tau, and UCHL-1 were measured with SIMOA, of P-Tau181, and the ratio P-Tau181/T-Tau with chemiluminescent immunoassay in 80 newly diagnosed MS patients who were followed up for three years with six-month Expanded Disability Status Scale (EDSS) assessments and yearly MRI scans.
RESULTS: Nineteen participants developing PIRA exhibited elevated GFAP and UCHL-1 levels, and reduced P-Tau181/T-Tau ratio. These biomarkers remained significant predictors of the outcome after adjusting for confounders, particularly older age at onset and higher baseline EDSS. Additionally, we identified moderate positive correlations between NfL-GFAP, NfL-UCHL-1, and GFAP-UCHL-1 levels, and moderate negative correlations between P-Tau181/T-Tau ratio and NfL, GFAP, and UCHL-1 levels.
CONCLUSIONS: The elevation of GFAP and UCHL-1 likely reflects the role of astrocytic activation, while the reduction of the P-Tau181/T-Tau ratio may indicate disrupted Tau metabolism in individuals at risk of PIRA. Our findings suggest that combining these innovative biomarkers with clinical risk factors could improve early prognostic accuracy.