Utilizing multiple in silico analyses to identify putative causal SCN5A variants in brugada syndrome

Jyh Ming Jimmy Juang, Tzu Pin Lu, Liang Chuan Lai, Chia Hsiang Hsueh, Yen Bin Liu, Chia Ti Tsai, Lian Yu Lin, Chih Chieh Yu, Juey Jen Hwang, Fu Tien Chiang, Sherri Shih Fan Yeh, Wen Pin Chen, Eric Y. Chuang, Ling Ping Lai, Jiunn Lee Lin

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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 14â€...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.

Original languageEnglish
Article number3850
JournalScientific Reports
Volume4
DOIs
Publication statusPublished - Jan 27 2014
Externally publishedYes

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Juang, J. M. J., Lu, T. P., Lai, L. C., Hsueh, C. H., Liu, Y. B., Tsai, C. T., Lin, L. Y., Yu, C. C., Hwang, J. J., Chiang, F. T., Yeh, S. S. F., Chen, W. P., Chuang, E. Y., Lai, L. P., & Lin, J. L. (2014). Utilizing multiple in silico analyses to identify putative causal SCN5A variants in brugada syndrome. Scientific Reports, 4, [3850]. https://doi.org/10.1038/srep03850