Despite urinary biomarkers being successfully used to diagnose and monitor a range of central nervous system disorders, including demyelinating, neurodegenerative, and motor neuron diseases, disease-specific metabolomic changes have not been identified for spinal muscular atrophy (SMA).
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SMA is a disabling and life-limiting inherited neuromuscular disease. It arises when homozygous deletions and/or loss-of-function mutations occur in the survival motor neuron 1 gene (SMN1). It causes muscle weakness that makes it difficult for affected children to move and can cause problems with swallowing and breathing. The four subtypes of SMA vary markedly in severity, with SMA1 causing premature death within the first few years of life. In contrast, patients with SMA3 or SMA4 can generally lead a normal life without any reduction in life expectancy.
SMA has typically been managed with support programs to limit the impact of symptoms and improve quality of life. The recent development of novel treatments, such as SMN2 splicing modifiers and gene replacement therapies, has introduced the possibility to significantly improve the disease course of SMA.
These new therapies have been shown to improve clinical outcomes if administered in the early stages of the disease. Unfortunately, this poses a considerable challenge since there are no precise, reliable biomarkers for diagnosing SMA. The absence of biomarkers also precludes the effective SMA screening of newborns and makes the implementation of individualized therapy highly challenging.
The lack of precise, predictive biomarkers means that treatment decisions are currently based on the quantification of SMN2 copy numbers, which has only moderate genotype–phenotype correlation. Consequently, some patients that are not eligible for the new treatments yet would have benefited from such intervention, whereas others are being treated unnecessarily.
There is thus an urgent need for more effective and robust biomarkers for the diagnosis and monitoring of SMA, which will enable better patient outcomes through more effective treatment. A recent publication of preliminary data obtained by researchers in Germany raises hope that urinary metabolic profiling using 1H nuclear magnetic resonance (NMR) could provide an effective non-invasive supportive tool* for the diagnosis and prognostic evaluation of SMA.
SMA urinary metabolic signatures were studied in urine samples collected from 29 children and adolescents with SMA of varying severity, 18 patients with Duchenne muscular dystrophy (DMD) and 444 healthy controls. A Bruker IVDr System* (Bruker Avance III HD 600MHz NMR spectrometer) was used to analyze the samples according to a highly standardized NMR protocol.
The spectra obtained were compared using machine-learning algorithms to search for potential biomarkers specific to SMA. A set of prediction models was developed based on this evaluation of the urinary metabolic fingerprints that enabled differential diagnosis of SMA based on urine NMR spectra alone. The models successfully discriminated patients with SMA from healthy controls and from patients with DMD. Furthermore, analysis of NMR urine metabolite profiles also distinguished between the different subtypes of SMA. In addition, the models effectively identified SMA in pre-symptomatic infants, which would enable newborn screening to identify infants at risk of developing symptomatic SMA and early treatment initiation to mitigate the severity of the ensuing disease.
These data raise hopes that urinary metabolic profiling using 1H NMR would enable early diagnosis of SMA and prediction of disease course, allowing treatment to be tailored accordingly, thereby improving patient outcomes.
*Bruker NMR Instruments are for Research Use Only. Not for use in clinical diagnostic procedures.
References
- Published by Saffari, A., Cannet, C., Blaschek, A. et al. Orphanet J Rare Dis 16, 441 (2021). https://doi.org/10.1186/s13023-021-02075-x
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