在DiscoverEHR研究中的50726个全外体序列中,功能变异的分布和临床影响
Frederick E Dewey1, Michael F Murray2, John D Overton3
1Regeneron Genetics Center, Tarrytown, NY 10591, USA. djcarey@geisinger.edu frederick.dewey@regeneron.com.
概括
该研究将超过5万名参与者的遗传数据与电子健康记录 (EHR) 联系起来,发现与健康特征相关的罕见遗传变异,并确定可用于精准医学的遗传信息.
科学领域:
- 基因组学
- 精准医学
- 生物信息学
背景情况:
- 发现EHR合作将高通量测序与Geisinger健康系统的电子健康记录 (EHR) 整合在一起.
- 这一举措旨在利用大规模的遗传和临床数据进行医学研究.
研究的目的:
- 使用大型综合数据集识别罕见的遗传变异及其与临床表型的关联.
- 探索基因组指导的治疗发现和精准医学的潜力.
主要方法:
- 在DiscovEHR研究中对50,726名成年参与者的全外体序列测定.
- 识别和分析罕见的单核酸变体和插入/删除事件.
- 将遗传数据与EHR衍生的临床表型联系起来.
主要成果:
- 发现大约420万种罕见变异,预计约有176,000种会导致基因功能丧失.
- 确定支持治疗点的临床关联,包括降脂基因.
- 检测与脂质和血液水平特征相关的以前未知的罕见基因.
- 发现3.5%的个体携带76个临床可操作基因的有害变体.
结论:
- 发现EHR数据集是精准医学和新疗法发现的宝贵资源.
- 这项研究强调了将大规模基因组数据与临床信息整合起来,
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