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

Research output: Contribution to journalArticle

12 Citations (Scopus)

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

Fingerprint

Brugada Syndrome
Computer Simulation
Secondary Protein Structure
Mutation
Sudden Cardiac Death
Computational Biology
DNA Sequence Analysis
Heart Diseases
Mass Spectrometry
Odds Ratio
In Vitro Techniques

ASJC Scopus subject areas

  • General

Cite this

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

In: Scientific Reports, Vol. 4, 3850, 27.01.2014.

Research output: Contribution to journalArticle

Juang, JMJ, Lu, TP, Lai, LC, Hsueh, CH, Liu, YB, Tsai, CT, Lin, LY, Yu, CC, Hwang, JJ, Chiang, FT, Yeh, SSF, Chen, WP, Chuang, EY, Lai, LP & Lin, JL 2014, 'Utilizing multiple in silico analyses to identify putative causal SCN5A variants in brugada syndrome', Scientific Reports, vol. 4, 3850. https://doi.org/10.1038/srep03850
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. / Utilizing multiple in silico analyses to identify putative causal SCN5A variants in brugada syndrome. In: Scientific Reports. 2014 ; Vol. 4.
@article{225e4fef52c84cb797a4694cfed63e33,
title = "Utilizing multiple in silico analyses to identify putative causal SCN5A variants in 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{\^a}€...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.",
keywords = "Brugada syndrome, SCN5A protein, human, sodium channel Nav1.5",
author = "Juang, {Jyh Ming Jimmy} and Lu, {Tzu Pin} and Lai, {Liang Chuan} and Hsueh, {Chia Hsiang} and Liu, {Yen Bin} and Tsai, {Chia Ti} and Lin, {Lian Yu} and Yu, {Chih Chieh} and Hwang, {Juey Jen} and Chiang, {Fu Tien} and Yeh, {Sherri Shih Fan} and Chen, {Wen Pin} and Chuang, {Eric Y.} and Lai, {Ling Ping} and Lin, {Jiunn Lee}",
year = "2014",
month = "1",
day = "27",
doi = "10.1038/srep03850",
language = "English",
volume = "4",
journal = "Scientific Reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",

}

TY - JOUR

T1 - Utilizing multiple in silico analyses to identify putative causal SCN5A variants in brugada syndrome

AU - Juang, Jyh Ming Jimmy

AU - Lu, Tzu Pin

AU - Lai, Liang Chuan

AU - Hsueh, Chia Hsiang

AU - Liu, Yen Bin

AU - Tsai, Chia Ti

AU - Lin, Lian Yu

AU - Yu, Chih Chieh

AU - Hwang, Juey Jen

AU - Chiang, Fu Tien

AU - Yeh, Sherri Shih Fan

AU - Chen, Wen Pin

AU - Chuang, Eric Y.

AU - Lai, Ling Ping

AU - Lin, Jiunn Lee

PY - 2014/1/27

Y1 - 2014/1/27

N2 - 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.

AB - 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.

KW - Brugada syndrome

KW - SCN5A protein, human

KW - sodium channel Nav1.5

UR - http://www.scopus.com/inward/record.url?scp=84893295763&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84893295763&partnerID=8YFLogxK

U2 - 10.1038/srep03850

DO - 10.1038/srep03850

M3 - Article

VL - 4

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

M1 - 3850

ER -