Literature DB >> 20139917

Prediction of the clinical phenotype of Fabry disease based on protein sequential and structural information.

Seiji Saito1, Kazuki Ohno, Jun Sese, Kanako Sugawara, Hitoshi Sakuraba.   

Abstract

Fabry disease is a genetic disorder caused by a deficiency of alpha-galactosidase, exhibiting a wide clinical spectrum, from the early-onset severe 'classic' form to the late-onset mild 'variant' one. Recent screening of newborns revealed that the incidence of Fabry disease is unexpectedly high, and that the genotypes of patients with this disease are quite heterogeneous and many novel mutations have been identified in them. This suggests that a lot of Fabry patients will be found in an early clinical stage when the prognosis is obscure and a proper therapeutic schedule for them cannot be determined. Thus, it is significant to predict the clinical phenotype of this disease resulting from a novel mutation. Herein, we proposed a phenotype prediction model based on sequential and structural information. As far as we know, this is the first report of phenotype prediction for Fabry disease. First, we investigated the sequential and structural changes in the alpha-galactosidase molecule responsible for Fabry disease. The results showed that there are quite large differences in several properties between the classic and variant groups. We then developed a phenotype prediction model involving the decision tree technique. The accuracy of this prediction model is high (86%), and Matthew's correlation coefficient is also high (0.49). The phenotype predictor proposed in this paper may be useful for determining a proper therapeutic schedule for this disease.

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Year:  2010        PMID: 20139917     DOI: 10.1038/jhg.2010.5

Source DB:  PubMed          Journal:  J Hum Genet        ISSN: 1434-5161            Impact factor:   3.172


  10 in total

1.  Predicting gene phenotype by multi-label multi-class model based on essential functional features.

Authors:  Lei Chen; Zhandong Li; Tao Zeng; Yu-Hang Zhang; Hao Li; Tao Huang; Yu-Dong Cai
Journal:  Mol Genet Genomics       Date:  2021-04-29       Impact factor: 3.291

2.  The use of classification trees for bioinformatics.

Authors:  Xiang Chen; Minghui Wang; Heping Zhang
Journal:  Wiley Interdiscip Rev Data Min Knowl Discov       Date:  2011-01-06

3.  Taming molecular flexibility to tackle rare diseases.

Authors:  Maria Vittoria Cubellis; Marc Baaden; Giuseppina Andreotti
Journal:  Biochimie       Date:  2015-04-02       Impact factor: 4.079

4.  Comparative study of structural changes caused by different substitutions at the same residue on α-galactosidase A.

Authors:  Seiji Saito; Kazuki Ohno; Hitoshi Sakuraba
Journal:  PLoS One       Date:  2013-12-26       Impact factor: 3.240

Review 5.  The Large Phenotypic Spectrum of Fabry Disease Requires Graduated Diagnosis and Personalized Therapy: A Meta-Analysis Can Help to Differentiate Missense Mutations.

Authors:  Valentina Citro; Marco Cammisa; Ludovica Liguori; Chiara Cimmaruta; Jan Lukas; Maria Vittoria Cubellis; Giuseppina Andreotti
Journal:  Int J Mol Sci       Date:  2016-12-01       Impact factor: 5.923

6.  Challenging popular tools for the annotation of genetic variations with a real case, pathogenic mutations of lysosomal alpha-galactosidase.

Authors:  Chiara Cimmaruta; Valentina Citro; Giuseppina Andreotti; Ludovica Liguori; Maria Vittoria Cubellis; Bruno Hay Mele
Journal:  BMC Bioinformatics       Date:  2018-11-30       Impact factor: 3.169

7.  Peripheral mitochondrial function correlates with clinical severity in idiopathic Parkinson's disease.

Authors:  Chiara Milanese; César Payán-Gómez; Marta Galvani; Nicolás Molano González; Maria Tresini; Soraya Nait Abdellah; Willeke M C van Roon-Mom; Silvia Figini; Johan Marinus; Jacobus J van Hilten; Pier G Mastroberardino
Journal:  Mov Disord       Date:  2019-05-28       Impact factor: 10.338

8.  Functional characterisation of alpha-galactosidase a mutations as a basis for a new classification system in fabry disease.

Authors:  Jan Lukas; Anne-Katrin Giese; Arseni Markoff; Ulrike Grittner; Ed Kolodny; Hermann Mascher; Karl J Lackner; Wolfgang Meyer; Phillip Wree; Viatcheslav Saviouk; Arndt Rolfs
Journal:  PLoS Genet       Date:  2013-08-01       Impact factor: 5.917

9.  Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.

Authors:  Jaie Woodard; Wei Zheng; Yang Zhang
Journal:  PLoS Comput Biol       Date:  2021-09-16       Impact factor: 4.475

10.  Screening of Fabry disease in patients with chronic kidney disease in Japan.

Authors:  Akiko Nagata; Makoto Nasu; Yusuke Kaida; Yosuke Nakayama; Yuka Kurokawa; Nao Nakamura; Ryo Shibata; Takuma Hazama; Takahiro Tsukimura; Tadayasu Togawa; Seiji Saito; Hitoshi Sakuraba; Kei Fukami
Journal:  Nephrol Dial Transplant       Date:  2021-12-31       Impact factor: 5.992

  10 in total

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