在医疗记录中报告的从家族关系中推断的疾病遗传性
Fernanda C G Polubriaginof1, Rami Vanguri1, Kayla Quinnies2
1Department of Biomedical Informatics, Columbia University, New York, NY, USA.
Cell
|May 22, 2018
概括
电子健康记录 (EHR) 可以识别数以百万计的家族关系, 这项研究验证了用于计算疾病遗传性的电子健康记录,为了解遗传疾病原因提供了可扩展的方法.
科学领域:
- 遗传学
- 生物信息学
- 流行病学
背景情况:
- 遗传性研究对于了解疾病病因至关重要,但传统上需要广泛收集患者数据.
- 电子健康记录 (EHR) 为生物医学研究提供了大量被动收集的数据资源.
- 电子健康记录中的近亲信息一直是未充分利用的研究资源.
研究的目的:
- 调查EHR衍生的家族关系对遗传性研究的有用性.
- 评估使用EHR数据来计算多种疾病表型的遗传性估计的可行性.
- 验证电子健康记录作为基因和疾病研究的可扩展资源.
主要方法:
- 挖掘来自三个学术医疗中心的紧急联系数据以确定家庭关系.
- 使用已识别的关系来计算500种疾病表型的遗传概率.
- 通过与现有文献以及不同地点对比EHR推导的遗传性估计.
主要成果:
- 在保持患者隐私的同时, 通过电子健康记录成功识别了740万个家庭关系.
- 来自EHR的家族关系与遗传推断的亲属关系一致.
- 对500种疾病表型的遗传性估计与之前的研究和机构之间的研究基本一致.
结论:
- 电子健康记录,特别是亲属数据,是遗传研究的宝贵和可扩展的资源.
- 该研究验证了用于计算疾病遗传性的电子健康记录,并补充了传统方法.
- 这些发现突显了电子健康记录有助于我们更好地了解疾病的遗传基础.
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