Rapid Identification of New Biomarkers for the Classification of GM1 Type 2 Gangliosidosis Using an Unbiased 1H NMR-Linked Metabolomics Strategy

Biomarkers currently available for the diagnosis, prognosis, and therapeutic monitoring of GM1 gangliosidosis type 2 (GM1T2) disease are mainly limited to those discovered in targeted proteomic-based studies. In order to identify and establish new, predominantly low-molecular-mass biomarkers for this disorder, we employed an untargeted, multi-analyte approach involving high-resolution H-1 NMR analysis coupled to a range of multivariate analysis and computational intelligence technique (CIT) strategies to explore biomolecular distinctions between blood plasma samples collected from GM1T2 and healthy control (HC) participants (n = 10 and 28, respectively). The relationship of these differences to metabolic mechanisms underlying the pathogenesis of GM1T2 disorder was also investigated. H-1 NMR-linked metabolomics analyses revealed significant GM1T2-mediated dysregulations in >= 13 blood plasma metabolites (corrected p < 0.04), and these included significant upregulations in 7 amino acids, and downregulations in lipoprotein-associated triacylglycerols and alanine. Indeed, results acquired demonstrated a profound distinctiveness between the GM1T2 and HC profiles. Additionally, employment of a genome-scale network model of human metabolism provided evidence that perturbations to propanoate, ethanol, amino-sugar, aspartate, seleno-amino acid, glutathione and alanine metabolism, fatty acid biosynthesis, and most especially branched-chain amino acid degradation (p = 10(-12)-10(-5)) were the most important topologically-highlighted dysregulated pathways contributing towards GM1T2 disease pathology. Quantitative metabolite set enrichment analysis revealed that pathological locations associated with these dysfunctions were in the order fibroblasts > Golgi apparatus > mitochondria > spleen approximate to skeletal muscle approximate to muscle in general. In conclusion, results acquired demonstrated marked metabolic imbalances and alterations to energy demand, which are consistent with GM1T2 disease pathogenesis mechanisms.

Automated summary

Using H-1 NMR analyses and multivariate analysis techniques, significant dysregulations in blood plasma metabolites of GM1T2 patients, particularly in amino acids and lipoprotein-associated triacylglycerols, were identified. The utilization of a genome-scale network model highlighted the importance of perturbations in various metabolic pathways towards GM1T2 disease pathology.