迪斯科瓦里:一个基于网络的精确医学工具,用于预测心肌病和通道病相关基因的变异性致病性
Leonie M Kurzlechner1, Sujata Kishnani1, Shawon Chowdhury1
1Department of Pediatrics, Division of Pediatric Cardiology (LMK, SK, SC, SLA, MEM-M, LEP, MBR, LAP, APL), Duke University School of Medicine, Durham, NC.
Circulation. Genomic and precision medicine
|July 6, 2023
概括
基因检测的进步增加了偶然发现的心脏病变体. 一个新的工具DiscoVari,使用信号对噪声分析来识别致病热点,改善突发心脏死亡风险的变异解释.
科学领域:
- 遗传学和基因组学 遗传学和基因组学
- 心血管医学 心血管医学
- 生物信息学是一种生物信息学.
背景情况:
- 基因检测越来越多地识别了与心脏病相关的偶然基因变异.
- 这些变异可能会造成心脏突然死亡的风险,需要准确的诊断解释.
- 越来越需要工具来评估这些变种的病原性.
研究的目的:
- 在与心脏突然死亡相关的基因中识别致病热点.
- 开发一个基于网络的精确医学工具,DiscoVari,以改进变种评估.
- 为了利用氨基酸水平的信号对噪声 (S:N) 分析来解释变异.
主要方法:
- 通过对健康人群的病原变异小等位基频率进行正常化,计算了氨基酸水平S:N比率.
- 定义的致病热点是氨基酸超过基因特异性的S:N值.
- 使用JavaScript,ReactJS,Next.js和NodeJS开发了DiscoVari;使用ClinVar和临床队列数据进行了验证.
主要成果:
- 与良性变异 (17.8%) 相比,DiscoVari在热点中发现了更高比例的可能致病性/致病性变异 (43.1%) 和良性变异 (17.8%).
- 大多数被重新归类为致病性 (75.3%) 和临床致病性变体 (73.1%) 的变体都位于已识别的热点内.
- 在热点中没有从临床队列中发现可能的良性/良性变异,这表明特异性很高.
结论:
- 迪斯科瓦里有效地通过使用氨基酸特定的S:N比率来识别易患疾病的氨基酸残留物.
- 该工具有助于可靠评估与心脏病相关的遗传变异.
- 迪斯科瓦里代表了心脏病学准确医学的宝贵资源.
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