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The molecular basis of lysosomal storage diseases and their treatment

Winchester, B., Vellodi, A., Young, E.·2000·Biochemical Society Transactions

Abstract

The lysosomal system is the main intracellular mechanism for the catabolism of naturally occurring endogenous and exogenous macromolecules and the subsequent recycling of their constituent monomeric components. It also plays an important part in processing essential metabolites. A genetic defect in a protein responsible for maintaining the lysosomal system results in the accumulation within lysosomes of partially degraded molecules, the initial step in the process leading to a lysosomal storage disease. The defective protein can be a luminal lysosomal enzyme or protein cofactor, a lysosomal membrane protein or a protein involved in the post-translational modification or transport of lysosomal proteins. Over 40 lysosomal storage diseases are known and they have a collective incidence of ≈ 1 in 7000–8000 live births. Most of the genes for the lysosomal proteins have been cloned, permitting mutation analysis in individual cases. This information can be used for genotype/phenotype correlation, genetic counselling and the selection of patients for novel forms of therapy, such as substrate deprivation or dispersal, enzyme replacement, bone-marrow transplantation and gene transfer.

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Metadata

Authors
Winchester, B., Vellodi, A., & Young, E.
Venue
Biochemical Society Transactions
Published
2000-02-01
Volume
28
Issue
2
Pages
150-154
ISSN
  • 0300-5127 (ISSN-L)
  • 1470-8752
OpenAlex
W36849100
Cited by
178
References
0
FWCI
2.27
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The molecular basis of lysosomal storage diseases and their treatment. https://app.cochat.ai/papers/10.1042/bst0280150
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Winchester, B., Vellodi, A., & Young, E. (2000). The molecular basis of lysosomal storage diseases and their treatment. Biochemical Society Transactions. https://doi.org/10.1042/bst0280150

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.