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Genotype-phenotype correlation of gangliosidosis mutations using in silico tools and homology modeling
- Source :
- Molecular Genetics and Metabolism Reports, Vol 20, Iss , Pp - (2019)
- Publication Year :
- 2019
- Publisher :
- Elsevier, 2019.
-
Abstract
- Gangliosidoses, including GM1-gangliosidosis and GM2-gangliosidosis (Tay-Sachs disease and Sandhoff disease), are lysosomal disorders resulting from enzyme deficiencies and accumulation of gangliosides. Phenotypes of gangliosidoses range from infantile, late-infantile, juvenile, and to the adult form. The genotype-phenotype correlation is essential for prognosis and clinical care planning for patients with a gangliosidosis condition. Previously, we have developed a method to establish the genotype-phenotype correlation of another lysosomal disease, mucopolysaccharidosis type I, with in silico tools. This same method was applied to analyze the genotype and phenotype of 38 patients diagnosed with a gangliosidosis disease in the United States. Out of 40 mutations identified, 3 were novel, including p.Tyr192His and p.Phe556Ser of the GLB1 gene and p.Gly461Val of the HEXA gene. Furthermore, the mutant protein structure of all missense mutations was constructed by homology modeling. A systemic structural analysis of these models revealed the specific mechanisms of how each mutation may lead to the disease. In summary, the method developed in this study holds promise as a tool that can be broadly applicable to other lysosomal diseases and monogenic diseases. Keywords: Genotype-phenotype correlation, In silico, Gangliosidosis, Disease subtype, Lysosomal disorder
- Subjects :
- Medicine (General)
R5-920
Biology (General)
QH301-705.5
Subjects
Details
- Language :
- English
- ISSN :
- 22144269
- Volume :
- 20
- Issue :
- -
- Database :
- Directory of Open Access Journals
- Journal :
- Molecular Genetics and Metabolism Reports
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.654d39930c6641c9b0e1552105eb82f9
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.ymgmr.2019.100495