我们所有人的多样性和规模在情境上改善了多基因预测,对代表性不足的人口进行了最大的改进
Kristin Tsuo1,2,3, Zhuozheng Shi4, Tian Ge2,5,6,7
1Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
bioRxiv : the preprint server for biology
|August 16, 2024
概括
多种基因组数据,包括来自我们所有人研究计划的数据,改善了代表性不足的群体的多基因风险得分 (PRS). 结合不同的数据集可以提高PRS的准确性,特别是对于历史上被排除在基因组研究之外的个体.
科学领域:
- 基因组学就是基因组学.
- 精准医学是一门精准的医学.
- 人口健康 人口健康
背景情况:
- 多基因风险评分 (PRS) 显示出预测疾病风险的前景.
- 由于培训数据的多样性有限,现有的PRS模型在代表性不足的人群中往往表现不佳.
- 大规模,多样化的生物银行对于提高PRS准确性和公平性至关重要.
研究的目的:
- 开发和评估多祖先,多生物库的多基因风险评分.
- 评估队列多样性对各种特征的PRS准确性的影响.
- 用不同的方法和生物库数据组合来比较PRS性能.
主要方法:
- 在"我们所有人" (AoU) 研究计划中为245,388个不同个体生成全基因组序列.
- 将AoU数据与英国生物银行 (UKB) 数据 (约50万参与者) 结合起来,用于32个复杂特征的PRS培训.
- 评估了在AoU参与者的持久,祖先多样化的子集中的PRS准确性,并比较了不同的数据和方法组合.
主要成果:
- 培训数据的多样性增加,特别是来自AoU的培训数据,显著改善了PRS在代表性不足的人群中的表现.
- 结合来自AoU和UKB的发现数据并不总是最优的;仅AoU的数据在非洲祖先人口中的某些特征的准确性更高.
- 个人级别的PRS准确性显示出线性衰变与祖先分歧,在使用多祖先基因组广泛协会研究 (GWAS) 数据时,衰变斜率较小.
结论:
- 具有平衡人类多样性的生物库,如AoU,对于创建公平而准确的多基因风险评分至关重要.
- 根据特定的特征和祖先来定制PRS训练数据可以优化预测准确性.
- 在精准医学应用中,个性化PRS准确性评估至关重要.
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