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1H-NMR-based metabolic profiling identifies non-invasive diagnostic and predictive urinary fingerprints in 5q spinal muscular atrophy by Saffari, Afshin (author);Cannet, Claire (author);Blaschek, Astrid (author);Hahn, Andreas (author);Hoffmann, Georg F. (author);Johannsen, Jessika (author);Kirsten, Romy (author);Kockaya, Musa (author);Kölker, Stefan (author);Müller-Felber, Wolfgang (author);Roos, Andreas (author);Schäfer, Hartmut (author);Schara, Ulrike (author);Spraul, Manfred (author);Trefz, Friedrich K. (author);Vill, Katharina (author);Wick, Wolfgang (author);Weiler, Markus (author);Okun, Jürgen G. (author);Ziegler, Andreas (author) is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is 1H-NMR-based metabolic profiling identifies non-invasive diagnostic and predictive urinary fingerprints in 5q spinal muscular atrophy about?

## Abstract ## Background 5q spinal muscular atrophy (SMA) is a disabling and life-limiting neuromuscular disease. In recent years, novel therapies have shown to improve clinical outcomes. Yet, the absence of reliable biomarkers renders clinical assessment and prognosis of possibly already affected newborns with a positive newborn screening result for SMA imprecise and difficult. Therapeutic decisions and stratification of individualized therapies remain challenging, especially in symptomatic children. The aim of this proof-of-concept and feasibility study was to explore the value of ^1^H-nuclear magnetic resonance (NMR)-based metabolic profiling in identifying non-invasive diagnostic and prognostic urinary fingerprints in children and adolescents with SMA. ## Results Urine samples were collected from 29 treatment-naïve SMA patients (5 pre-symptomatic, 9 SMA 1, 8 SMA 2, 7 SMA 3), 18 patients with Duchenne muscular dystrophy (DMD) and 444 healthy controls. Using machine-learning algorithms, we propose a set of prediction models built on urinary fingerprints that showed potential diagnostic value in discriminating SMA patients from controls and DMD, as well as predictive properties i

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Author

Saffari, Afshin (author);Cannet, Claire (author);Blaschek, Astrid (author);Hahn, Andreas (author);Hoffmann, Georg F. (author);Johannsen, Jessika (author);Kirsten, Romy (author);Kockaya, Musa (author);Kölker, Stefan (author);Müller-Felber, Wolfgang (author);Roos, Andreas (author);Schäfer, Hartmut (author);Schara, Ulrike (author);Spraul, Manfred (author);Trefz, Friedrich K. (author);Vill, Katharina (author);Wick, Wolfgang (author);Weiler, Markus (author);Okun, Jürgen G. (author);Ziegler, Andreas (author)

Publisher

Springer Science and Business Media LLC

Published

2021

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)