ReviewJournal of neurology2025
Advancing personalized spinal muscular atrophy care: matching the right biomarker to the right patient at the right time.
Review in Journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Retrospective analysis of spinal muscular atrophy in tunisian population: phenotypic-genotypic associations and considerations for therapeutic advancement.Neurogenetics · 2026Article
- Unveiling the Mysteries of CLEC3B: Physiological Roles, Pathological Impacts, and Research Gaps.Cells · 2026Review
- Pre-symptomatic treatment of spinal muscular atrophy: a strategic shift from concept to clinical practice.World journal of pediatrics : WJP · 2026Article
- RNA biomarkers in spinal muscular atrophy: enhancing pathogenesis understanding and guiding precision medicine.Cellular and molecular life sciences : CMLS · 2026Review
- Behavioral barriers in the management of spinal muscular atrophy: The role of procrastination, regret, and burnout.PloS one · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the advent of survival motor neuron (SMN)-enhancing therapies, the natural course of spinal muscular atrophy (SMA) has been reshaped, unveiling new patient phenotypes. As therapeutic options expand, there is an increasing demand for robust biomarkers to enhance prognostic accuracy, anticipate treatment response, track disease progression, and support personalized clinical decision-making. This narrative review critically examines the literature and discusses the role and appropriate application of key biomarkers across different age groups, ranging from presymptomatic newborns to adults with chronic disease. Genetic testing remains the diagnostic gold standard, with SMN2 copy number serving as the strongest prognostic indicator. However, substantial phenotypic variability exists among individuals with the same SMN2 copy number. Neurophysiological measures, including compound muscle action potential (CMAP) and motor unit number estimation (MUNE), accurately inform about motor neuron integrity, often anticipating clinical changes and potentially predicting treatment responsiveness. Circulating neurofilaments (NF) are increasingly recognized as sensitive biomarkers of active neurodegeneration. While NF holds promise in infants and younger children, its relevance in adolescents and adults remains limited. Conversely, quantitative muscle imaging techniques, such as MRI and ultrasound, may be valuable tools in adolescent and adult patients, capturing long-term muscle structural changes. By reviewing the current evidence across age groups, we provide an overview of biomarker application in newborns, children and adolescents/adults for diagnostic, prognostic, predictive, and monitoring purposes to help advance individualized management across all SMA stages.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.