选择,优化和验证10个慢性病多基因风险评分,以在美国多种不同人群中临床实施
Niall J Lennon1, Leah C Kottyan2, Christopher Kachulis3
1Broad Institute of MIT and Harvard, Cambridge, MA, USA. nlennon@broadinstitute.org.
Nature medicine
|February 20, 2024
概括
电子医疗记录和基因组学 (eMERGE) 网络开发了一个框架,用于返回多基因风险得分 (PRS) 在多种人群中. 这使得在临床环境中对心脏病和癌症等疾病的基因组信息风险评估成为可能.
科学领域:
- 基因组学和精准医学精准医学
- 临床实施科学 临床实施科学
- 生物信息学是一种生物信息学.
背景情况:
- 多基因风险评分 (PRS) 是有前途的,但在不同人群和临床解释中面临挑战.
- 实施PRS需要解决预测性绩效差异,并为提供者和患者制定有效的沟通策略.
研究的目的:
- 开发和测试一个框架和管道,用于在多样化的临床研究群体中返回基于PRS的基因组信息风险评估.
- 为具有临床实用性的疾病选择和实施PRS,重点关注心脏代谢疾病和癌症.
- 建立一个监管合规和临床报告PRS结果的途径.
主要方法:
- 在临床研究中,为25000名不同的成人和儿童返回PRS结果开发了一个框架.
- 根据性能,可操作性和实用性,选择了PRS实施的十个条件,优先考虑非洲和西班牙裔人口中的证据.
- 创建了一个临床PRS实施管道,包括使用多样化的队列数据进行得分转移,验证和遗传祖先校准.
主要成果:
- 建立了临床PRS实施的管道,包括验证和验证流程.
- 利用遗传祖先数据对PRS模型进行校准,提高了不同人群的表现.
- 为提供者开发了PRS临床报告和基因组信息风险评估框架.
结论:
- eMERGE网络的经验为在不同的临床环境中实施基于PRS的测试提供了一个模型.
- 开发的框架解决了PRS临床实用性的关键挑战,包括不同组的表现和结果解释.
- 这项工作有助于将基因组风险信息纳入常规临床护理.
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