A glycomic workflow for LC-MS/MS analysis of urine glycosaminoglycan biomarkers in mucopolysaccharidoses

Author:

Nilsson Jonas1,Persson Andrea2,Voronstov Egor1,Nikpour Mahnaz2,Noborn Fredrik2,Larson Göran2,Blomqvist Maria2

Affiliation:

1. Proteomics Core Facility, Sahlgrenska Academy, University of Gothenburg

2. Department of Laboratory Medicine, Institute of Biomedicine, University of Gothenburg

Abstract

Abstract In recent years, several rational designed therapies have been developed for treatment of mucopolysaccharidoses (MPS), a group of inherited metabolic disorders in which glycosaminoglycans (GAGs) are accumulated in various tissues and organs. Thus, improved disease-specific biomarkers for diagnosis and monitoring treatment efficacy are of paramount importance. Specific non-reducing end GAG structures (GAG-NREs) have become promising biomarkers for MPS, as the compositions of the GAG-NREs depend on the nature of the lysosomal enzyme deficiency, thereby creating a specific pattern for each subgroup. However, there is yet no straightforward clinical laboratory platform which can assay all MPS-related GAG-NREs in one single analysis. Here, we developed and applied a GAG domain mapping approach for analyses of urine samples of ten MPS patients with various MPS diagnoses and corresponding aged-matched controls. We describe a nano-LC-MS/MS method of GAG-NRE profiling, utilizing 2-aminobenzamide reductive amination labeling to improve the sensitivity and the chromatographic resolution. Diagnostic urinary GAG-NREs were identified for MPS types IH/IS, II, IIIc, IVa and VI, corroborating GAG-NRE as biomarkers for these known enzyme deficiencies. Furthermore, a significant reduction of diagnostic urinary GAG-NREs in MPS IH (n = 2) and MPS VI (n = 1) patients under treatment was demonstrated. We argue that this straightforward glycomic workflow, designed for the clinical analysis of MPS-related GAG-NREs in one single analysis, will be of value for expanding the use of GAG-NREs as biomarkers for MPS diagnosis and treatment monitoring.

Publisher

Research Square Platform LLC

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