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Utilizing multiple in silico analyses to identify putative causal SCN5A variants in Brugada syndrome Juang JM; Lu TP; Lai LC; Hsueh CH; Liu YB; Tsai CT; Lin LY; Yu CC; Hwang JJ; Chiang FT; Yeh SS; Chen WP; Chuang EY; Lai LP; Lin JLSci Rep 2014[Jan]; 4 (ä): 3850Brugada 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.|Adult[MESH]|Brugada Syndrome/*genetics[MESH]|Female[MESH]|Genetic Predisposition to Disease[MESH]|Humans[MESH]|Male[MESH]|Middle Aged[MESH]|NAV1.5 Voltage-Gated Sodium Channel/chemistry/*genetics[MESH]|Patch-Clamp Techniques[MESH]|Protein Structure, Secondary[MESH] |
