151. Utilizing Multiple in Silico Analyses to Identify Putative Causal SCN5A Variants in Brugada Syndrome
- Author
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Wen-Pin Chen, Eric Y. Chuang, Lian-Yu Lin, Ling Ping Lai, Jyh-Ming Jimmy Juang, Chia Ti Tsai, Fu-Tien Chiang, Tzu-Pin Lu, Chia Hsiang Hsueh, Jiunn Lee Lin, Sherri Shih Fan Yeh, Liang-Chuan Lai, Juey-Jen Hwang, Chih Chieh Yu, and Yen-Bin Liu
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Genetics ,Adult ,Male ,Multidisciplinary ,Patch-Clamp Techniques ,In silico ,fungi ,Biology ,Middle Aged ,medicine.disease ,DNA sequencing ,Protein Structure, Secondary ,Article ,NAV1.5 Voltage-Gated Sodium Channel ,medicine ,Humans ,Female ,Genetic Predisposition to Disease ,cardiovascular diseases ,Brugada syndrome ,Sequence (medicine) ,Brugada Syndrome - Abstract
Brugada syndrome (BrS) is an inheritable sudden cardiac death disease mainly caused by SCN5A mutations. Traditional approaches can be costly and time-consuming if all candidate variants need to be validated through in vitro studies. Therefore, we developed a new approach by combining multiple in silico analyses to predict functional and structural changes of candidate SCN5A variants in BrS before conducting in vitro studies. Five SCN5A non-synonymous variants (1651G>A, 1776C>G, 1673A>G, 3269C>T and 3578G>A) were identified in 14 BrS patients using direct DNA sequencing. Several bioinformatics algorithms were applied and predicted that 1651G>A (A551T) and 1776C>G (N592K) were high-risk SCN5A variants (odds ratio 59.59 and 23.93). The results were validated by Mass spectrometry and in vitro electrophysiological assays. We concluded that integrating sequence-based information and secondary protein structures elements may help select highly potential variants in BrS before conducting time-consuming electrophysiological studies and two novel SCN5A mutations were validated.
- Published
- 2014
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