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Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1
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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829143/ https://www.ncbi.nlm.nih.gov/pubmed/29487322 http://dx.doi.org/10.1038/s41598-018-22078-2 |
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author | Makino, Elina Klodnitsky, Helen Leonard, John Lillie, James Lund, Troy C. Marshall, John Nietupski, Jennifer Orchard, Paul J. Miller, Weston P. Phaneuf, Clifford Tietz, Drew Varban, Mariet L. Donovan, Marissa Belenki, Alexey |
author_facet | Makino, Elina Klodnitsky, Helen Leonard, John Lillie, James Lund, Troy C. Marshall, John Nietupski, Jennifer Orchard, Paul J. Miller, Weston P. Phaneuf, Clifford Tietz, Drew Varban, Mariet L. Donovan, Marissa Belenki, Alexey |
author_sort | Makino, Elina |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5829143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-58291432018-03-01 Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1 Makino, Elina Klodnitsky, Helen Leonard, John Lillie, James Lund, Troy C. Marshall, John Nietupski, Jennifer Orchard, Paul J. Miller, Weston P. Phaneuf, Clifford Tietz, Drew Varban, Mariet L. Donovan, Marissa Belenki, Alexey Sci Rep Article 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. Nature Publishing Group UK 2018-02-27 /pmc/articles/PMC5829143/ /pubmed/29487322 http://dx.doi.org/10.1038/s41598-018-22078-2 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Makino, Elina Klodnitsky, Helen Leonard, John Lillie, James Lund, Troy C. Marshall, John Nietupski, Jennifer Orchard, Paul J. Miller, Weston P. Phaneuf, Clifford Tietz, Drew Varban, Mariet L. Donovan, Marissa Belenki, Alexey Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1 |
title | Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1 |
title_full | Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1 |
title_fullStr | Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1 |
title_full_unstemmed | Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1 |
title_short | Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1 |
title_sort | fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829143/ https://www.ncbi.nlm.nih.gov/pubmed/29487322 http://dx.doi.org/10.1038/s41598-018-22078-2 |
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