ArticleCellular and molecular life sciences : CMLS2024
Proteomics profiling and machine learning in nusinersen-treated patients with spinal muscular atrophy.
Article in Cellular and molecular life sciences : CMLS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Proteomic alterations in cerebrospinal fluid of spinal muscular atrophy patients undergoing nusinersen therapy: a systematic review and meta-analysis of potential biomarkers of treatment response.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Pooled it
- Extracellular vesicles as biomarkers of disease progression and therapeutic response in patients with spinal muscular atrophy.Molecular therapy. Advances · 2026Article
- Longitudinal multi-omics profiling of spinal muscular atrophy.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026Article
- Pharmacokinetics of therapies approved for spinal muscular atrophy: A narrative review of current evidence.The Journal of international medical research · 2025Review
- Advancing personalized spinal muscular atrophy care: matching the right biomarker to the right patient at the right time.Journal of neurology · 2025Review
- Neuronal Pentraxin 2 as a Potential Biomarker for Nusinersen Therapy Response in Adults with Spinal Muscular Atrophy: A Pilot Study.Biomedicines · 2025Article
- Proteomic Profiling Towards a Better Understanding of Genetic Based Muscular Diseases: The Current Picture and a Look to the Future.Biomolecules · 2025Review
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Authors and funding
20 authors.
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Abstract
aimThe availability of disease-modifying therapies and newborn screening programs for spinal muscular atrophy (SMA) has generated an urgent need for reliable prognostic biomarkers to classify patients according to disease severity. We aim to identify cerebrospinal fluid (CSF) prognostic protein biomarkers in CSF samples of SMA patients collected at baseline (T0), and to describe proteomic profile changes and biological pathways influenced by nusinersen before the sixth nusinersen infusion (T302).
methodsIn this multicenter retrospective longitudinal study, we employed an untargeted liquid chromatography mass spectrometry (LC-MS)-based proteomic approach on CSF samples collected from 61 SMA patients treated with nusinersen (SMA1 n=19, SMA2 n=19, SMA3 n=23) at T0 at T302. The Random Forest (RF) machine learning algorithm and pathway enrichment analysis were applied for analysis.
resultsThe RF algorithm, applied to the protein expression profile of naïve patients, revealed several proteins that could classify the different types of SMA according to their differential abundance at T0. Analysis of changes in proteomic profiles identified a total of 147 differentially expressed proteins after nusinersen treatment in SMA1, 135 in SMA2, and 289 in SMA3. Overall, nusinersen-induced changes on proteomic profile were consistent with i) common effects observed in allSMA types (i.e. regulation of axonogenesis), and ii) disease severity-specific changes, namely regulation of glucose metabolism in SMA1, of coagulation processes in SMA2, and of complement cascade in SMA3.
conclusionsThis untargeted LC-MS proteomic profiling in the CSF of SMA patients revealed differences in protein expression in naïve patients and showed nusinersen-related modulation in several biological processes after 10 months of treatment. Further confirmatory studies are needed to validate these results in larger number of patients and over abroader timeframe.
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