SAAMP 2.0: an algorithm to predict genotype-phenotype correlation of lysosomal storage diseases.

SAAMP 2.0: an algorithm to predict genotype-phenotype correlation of lysosomal storage diseases.
Clin Genet. 2018 Feb 02;:
Authors: Ou L, Przybilla MJ, Whitley CB
Abstract
Lysosomal storage diseases (LSDs) are a group of genetic disorders, resulting from deficiencies of lysosomal enzyme. Genotype-phenotype correlation is essential for timely and proper treatment allocation. Recently, by integrating prediction outcomes of 7 bioinformatics tools, we developed a SAAMP algorithm to predict the impact of individual amino acid substitution. To optimize this approach, we evaluated the performance of these bioinformatics tools in a broad array of genes. PolyPhen and PROVEAN had the best performances, while SNP&GOs, PANTHER and I-Mutant had the worst performances. Therefore, SAAMP 2.0 was developed by excluding 3 tools with worst performance, yielding a sensitivity of 94% and a specificity of 90%. To generalize the guideline to proteins without known structures, we built the 3D model of iduronate-2-sulfatase by homology modeling. Further, we investigated the phenotype severity of known disease-causing mutations of the GLB1 gene, which lead to two LSDs (GM1 gangliosidosis; Morquio disease type B). Based on previous literature and structural analysis, we associated these mutations with disease subtypes and proposed a theory to explain the complicated genotype-phenotype correlation. Collectively, an updated guideline for phenotype prediction...

Source: Clinical Genetics - February 2, 2018 Category: Genetics & Stem Cells Authors: Ou L, Przybilla MJ, Whitley CB Tags: Clin Genet Source Type: research