| First Author | Makino E | Year | 2018 |
| Journal | Sci Rep | Volume | 8 |
| Issue | 1 | Pages | 3681 |
| PubMed ID | 29487322 | Mgi Jnum | J:263131 |
| Mgi Id | MGI:6162873 | Doi | 10.1038/s41598-018-22078-2 |
| Citation | Makino E, et al. (2018) Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1. Sci Rep 8(1):3681 |
| abstractText | Certain recessively inherited diseases result from an enzyme deficiency within lysosomes. In mucopolysaccharidoses (MPS), a defect in glycosaminoglycan (GAG) degradation leads to GAG accumulation followed by progressive organ and multiple system dysfunctions. Current methods of GAG analysis used to diagnose and monitor the diseases lack sensitivity and throughput. Here we report a LC-MS method with accurate metabolite mass analysis for identifying and quantifying biomarkers for MPS type I without the need for extensive sample preparation. The method revealed 225 LC-MS features that were >1000-fold enriched in urine, plasma and tissue extracts from untreated MPS I mice compared to MPS I mice treated with iduronidase to correct the disorder. Levels of several trisaccharides were elevated >10000-fold. To validate the clinical relevance of our method, we confirmed the presence of these biomarkers in urine, plasma and cerebrospinal fluid from MPS I patients and assessed changes in their levels after treatment. |
