Browsing by Author "Hwang, Juey-Jen"

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    Utilizing Multiple in Silico Analyses to Identify Putative Causal SCN5A Variants in Brugada Syndrome
    (Springer Nature, 2014-01-27) Juang, Jyh-Ming Jimmy; Lu, Tzu-Pin; Lai, Liang-Chuan; Hsueh, Chia-Hsiang; Liu, Yen-Bin; Tsai, Chia-Ti; Lin, Lian-Yu; Yu, Chih-Chieh; Hwang, Juey-Jen; Chiang, Fu-Tien; Yeh, Sherri Shih-Fan; Chen, Wen-Pin; Chuang, Eric Y.; Lai, Ling-Ping; Lin, Jiunn-Lee; Medicine, School of Medicine
    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.