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| Verfasst von: | Saffari, Afshin [VerfasserIn]  |
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| | Niesert, Moritz [VerfasserIn] |
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| | Cannet, Claire [VerfasserIn] |
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| | Blaschek, Astrid [VerfasserIn] |
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| | Hahn, Andreas [VerfasserIn] |
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| | Johannsen, Jessika [VerfasserIn] |
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| | Kockaya, Musa [VerfasserIn] |
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| | Kölbel, Heike [VerfasserIn] |
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| | Hoffmann, Georg F. [VerfasserIn] |
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| | Claus, Peter [VerfasserIn] |
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| | Kölker, Stefan [VerfasserIn] |
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| | Müller-Felber, Wolfgang [VerfasserIn] |
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| | Roos, Andreas [VerfasserIn] |
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| | Schara-Schmidt, Ulrike [VerfasserIn] |
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| | Trefz, Friedrich K. [VerfasserIn] |
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| | Vill, Katharina [VerfasserIn] |
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| | Wick, Wolfgang [VerfasserIn] |
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| | Weiler, Markus [VerfasserIn] |
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| | Okun, Jürgen G. [VerfasserIn] |
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| | Ziegler, Andreas [VerfasserIn] |
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| Titel: | 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 |
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| Verf.angabe: | 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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| E-Jahr: | 2024 |
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| Jahr: | 12 November 2024 |
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| Umfang: | 19 S. |
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| Illustrationen: | Illustrationen |
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| Fussnoten: | Die Ziffer 1 ist im Titel hochgestellt ; Gesehen am 20.05.2025 |
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| Titel Quelle: | Enthalten in: International journal of molecular sciences |
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| Ort Quelle: | Basel : Molecular Diversity Preservation International, 2000 |
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| Jahr Quelle: | 2024 |
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| Band/Heft Quelle: | 25(2024), 22, Artikel-ID 12123, Seite 1-19 |
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| ISSN Quelle: | 1422-0067 |
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| | 1661-6596 |
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| Abstract: | 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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| DOI: | doi:10.3390/ijms252212123 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
kostenfrei: Volltext: https://doi.org/10.3390/ijms252212123 |
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| | kostenfrei: Volltext: https://www.mdpi.com/1422-0067/25/22/12123 |
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| | DOI: https://doi.org/10.3390/ijms252212123 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | 1H-NMR spectroscopy |
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| | metabolic profiling |
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| | metabolomics |
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| | spinal muscular atrophy |
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| K10plus-PPN: | 1926080106 |
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| Verknüpfungen: | → Zeitschrift |
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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 / Saffari, Afshin [VerfasserIn]; 12 November 2024 (Online-Ressource)
