多种种群的基因分析有助于发现复杂的特征
Genevieve L Wojcik1, Mariaelisa Graff2, Katherine K Nishimura3
1Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
Nature
|June 21, 2019
概括
使用多元多民族参与者的大规模基因组研究至关重要. 使用基因组学和流行病学 (PAGE) 的人口结构研究确定了26种表型的新型遗传关联,突出了减少健康差异和改进精准医学的多样化数据的需要.
科学领域:
- 基因组学与人类遗传学
- 人口遗传学
- 精准医学
背景情况:
- 全基因组关联研究 (GWAS) 是理解复杂特征的基础,但主要基于欧洲祖先的数据.
- 在GWAS中不同种群的代表性不足会加剧健康差异,导致遗漏的发现,特别是在罕见的,特定种群的变异中.
- 基因架构和效应大小在不同种群之间有所不同,这限制了从非多样化的群体中得出的发现和风险预测得分的概括性.
研究的目的:
- 在大型基因组研究中展示多元化多民族参与者的价值.
- 开发和应用多民族和混合人口的分析策略.
- 确定非欧洲人的临床和行为表型的新遗传位置和关联.
主要方法:
- 通过使用基因组学和流行病学 (PAGE) 研究对49839名非欧洲人进行了26种临床和行为表型的全基因组关联研究 (GWAS).
- 采用定制策略来分析多民族和混合人口.
- 确定了新的位置,已知位置的二次信号,并复制了现有的GWAS目录协会.
主要成果:
- 在26个表型中确定了27个新的遗传位点和38个已知位点的次要信号.
- 在多样化的研究队列中复制了GWAS目录中的1444个关联.
- 对之前发表的GWAS协会的祖先效果大小异质性的观察证据,强调了对精细映射的多样性队列的好处.
结论:
- 多元化,多民族参与者对于最大限度地提高基因发现和确保获得精准医学的公平性至关重要.
- 为PAGE研究开发的分析框架为分析多种基因组数据提供了有价值的方法.
- 在不同的人群中持续大规模的基因组研究对于减少健康差异和推进个性化医疗保健至关重要.
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