Genotype-phenotype correlation of gangliosidosis mutations using in silico tools and homology modeling

Li Ou; Sarah Kim; Chester B Whitley; Jeanine R. Jarnes-Utz

doi:10.1016/j.ymgmr.2019.100495

Genotype-phenotype correlation of gangliosidosis mutations using in silico tools and homology modeling

Li Ou, Sarah Kim, Chester B Whitley, Jeanine R. Jarnes-Utz

Pediatrics - Genetics and Metabolism

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

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.

Original language	English (US)
Article number	100495
Journal	Molecular Genetics and Metabolism Reports
Volume	20
DOIs	https://doi.org/10.1016/j.ymgmr.2019.100495
State	Published - Sep 2019

Bibliographical note

Funding Information:
This work is supported by NIH grant P01HD032652. Dr. Li Ou is a fellow of the Lysosomal Disease Network (U54NS065768). The Lysosomal Disease Network is a part of the Rare Diseases Clinical Research Network (RDCRN), an initiative of the Office of Rare Diseases Research (ORDR), and NCATS. This consortium is funded through a collaboration between NCATS, the National Institute of Neurological Disorders and Stroke (NINDS), and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK).

Funding Information:
This work is supported by NIH grant P01HD032652 . Dr. Li Ou is a fellow of the Lysosomal Disease Network ( U54NS065768 ). The Lysosomal Disease Network is a part of the Rare Diseases Clinical Research Network (RDCRN), an initiative of the Office of Rare Diseases Research (ORDR), and NCATS. This consortium is funded through a collaboration between NCATS , the National Institute of Neurological Disorders and Stroke (NINDS), and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK).

Publisher Copyright:
© 2019 The Authors

Keywords

Disease subtype
Gangliosidosis
Genotype-phenotype correlation
In silico
Lysosomal disorder

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title = "Genotype-phenotype correlation of gangliosidosis mutations using in silico tools and homology modeling",

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.",

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Genotype-phenotype correlation of gangliosidosis mutations using in silico tools and homology modeling

Abstract

Bibliographical note

Keywords

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