Biochemical determinants for diagnosis and prediction of severity in 5q spinal muscular atrophy

Saffari A, Niesert M, Cannet C, Blaschek A, Hahn A, Johannsen J, Kockaya M, Kölbel H, Hoffmann GF, Claus P, et al. 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. International Journal of Molecular Sciences. 2024; 25(22):12123. https://doi.org/10.3390/ijms252212123

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.