ArticleJournal of clinical medicine2023
Cerebrospinal Fluid Proteomic Changes after Nusinersen in Patients with Spinal Muscular Atrophy.
Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- 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
- Cerebrospinal fluid metabolomics reveals predictive biomarkers of nusinersen therapy efficacy in type II and type III spinal muscular atrophy patients.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Article
- Long-term CSF responses in adult patients with spinal muscular atrophy type 2 or 3 on treatment with nusinersen.Journal of neurology · 2025Article
- Cerebrospinal fluid proteomic profiling reveals potential biomarkers and altered pathways in myotonic dystrophy type 1.Frontiers in neuroscience · 2025Article
- Proteomics profiling and machine learning in nusinersen-treated patients with spinal muscular atrophy.Cellular and molecular life sciences : CMLS · 2024Article
- Alteration of LARGE1 abundance in patients and a mouse model of 5q-associated spinal muscular atrophy.Acta neuropathologica · 2024Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
Disease-modifying treatments have transformed the natural history of spinal muscular atrophy (SMA), but the cellular pathways altered by SMN restoration remain undefined and biomarkers cannot yet precisely predict treatment response. We performed an exploratory cerebrospinal fluid (CSF) proteomic study in a diverse sample of SMA patients treated with nusinersen to elucidate therapeutic pathways and identify predictors of motor improvement. Proteomic analyses were performed on CSF samples collected before treatment (T0) and at 6 months (T6) using an Olink panel to quantify 1113 peptides. A supervised machine learning approach was used to identify proteins that discriminated patients who improved functionally from those who did not after 2 years of treatment. A total of 49 SMA patients were included (10 type 1, 18 type 2, and 21 type 3), ranging in age from 3 months to 65 years. Most proteins showed a decrease in CSF concentration at T6. The machine learning algorithm identified ARSB, ENTPD2, NEFL, and IFI30 as the proteins most predictive of improvement. The machine learning model was able to predict motor improvement at 2 years with 79.6% accuracy. The results highlight the potential application of CSF biomarkers to predict motor improvement following SMA treatment. Validation in larger datasets is needed.
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Registered trials
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