Identification of biochemical determinants for diagnosis and prediction of severity in 5q spinal muscular atrophy using 1H-nuclear magnetic resonance metabolic profiling in patient-derived biofluids
This study explores the potential of 1H-NMR spectroscopy-based metabolic profiling in various biofluids as a diagnostic and predictive modality to assess disease severity in individuals with 5q spinal muscular atrophy. A total of 213 biosamples (urine, plasma, and CSF) from 153 treatment-naïve pati...
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
12 November 2024
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| In: |
International journal of molecular sciences
Year: 2024, Jahrgang: 25, Heft: 22, Pages: 1-19 |
| ISSN: | 1422-0067 |
| DOI: | 10.3390/ijms252212123 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.3390/ijms252212123 Verlag, kostenfrei, Volltext: https://www.mdpi.com/1422-0067/25/22/12123 
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| Verfasserangaben: | Afshin Saffari, Moritz Niesert, Claire Cannet, Astrid Blaschek, Andreas Hahn, Jessika Johannsen, Musa Kockaya, Heike Kölbel, Georg F. Hoffmann, Peter Claus, Stefan Kölker, Wolfgang Müller-Felber, Andreas Roos, Ulrike Schara-Schmidt, Friedrich K. Trefz, Katharina Vill, Wolfgang Wick, Markus Weiler, Jürgen G. Okun and Andreas Ziegler |
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| 245 | 1 | 0 | |a Identification of biochemical determinants for diagnosis and prediction of severity in 5q spinal muscular atrophy using 1H-nuclear magnetic resonance metabolic profiling in patient-derived biofluids |c Afshin Saffari, Moritz Niesert, Claire Cannet, Astrid Blaschek, Andreas Hahn, Jessika Johannsen, Musa Kockaya, Heike Kölbel, Georg F. Hoffmann, Peter Claus, Stefan Kölker, Wolfgang Müller-Felber, Andreas Roos, Ulrike Schara-Schmidt, Friedrich K. Trefz, Katharina Vill, Wolfgang Wick, Markus Weiler, Jürgen G. Okun and Andreas Ziegler |
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| 520 | |a This study explores the potential of 1H-NMR spectroscopy-based metabolic profiling in various biofluids as a diagnostic and predictive modality to assess disease severity in individuals with 5q spinal muscular atrophy. A total of 213 biosamples (urine, plasma, and CSF) from 153 treatment-naïve patients with SMA across five German centers were analyzed using 1H-NMR spectroscopy. Prediction models were developed using machine learning algorithms which enabled the patients with SMA to be grouped according to disease severity. A quantitative enrichment analysis was employed to identify metabolic pathways associated with disease progression. The results demonstrate high sensitivity (84-91%) and specificity (91-94%) in distinguishing treatment-naïve patients with SMA from controls across all biofluids. The urinary and plasma profiles differentiated between early-onset (type I) and later-onset (type II/III) SMA with over 80% accuracy. Key metabolic differences involved alterations in energy and amino acid metabolism. This study suggests that 1H-NMR spectroscopy based metabolic profiling may be a promising, non-invasive tool to identify patients with SMA and for severity stratification, potentially complementing current diagnostic and prognostic strategies in SMA management. | ||
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| 650 | 4 | |a metabolic profiling | |
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