An algorithm for candidate sequencing in non-dystrophic skeletal muscle channelopathies View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-07

AUTHORS

Tai-Seung Nam, Christoph Lossin, Dong-Uk Kim, Myeong-Kyu Kim, Young-Ok Kim, Kang-Ho Choi, Seok-Yong Choi, Sang-Cheol Park, In-Seop Na

ABSTRACT

Human skeletal muscle channelopathies (HSMCs) are a group of heritable conditions with ion channel-related etiology and similar presentation. To create a comprehensive picture of the phenotypic spectrum for each condition and to devise a strategy that facilitates the differential diagnosis, we collected the genotype and phenotype information from more than 500 previously published HSMC studies. Using these records, we were able to identify clear correlations between particular clinical features and the underlying alteration(s) in the genes SCN4A, CACNA1S, KCNJ2, and CLCN1. This allowed us to develop a clinical, symptom-based, binary decision flow algorithm that predicts the proper genetic origin with high accuracy (0.88-0.93). The algorithm was implemented in a stand-alone online tool ("CGPS"- http://cgps.ddd.co.kr ) to assist with HSCM diagnosis in the clinical practice. The CGPS provides simple, symptom-oriented navigation that guides the user to the most likely molecular basis of the presentation, which permits highly targeted genetic screens and, upon confirmation, tailored pharmacotherapy based on the molecular origin. More... »

PAGES

1770-1777

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00415-013-6872-8

DOI

http://dx.doi.org/10.1007/s00415-013-6872-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1045047682

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23456025


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