Polygenic risk scores and health disparities: the role of blood cells immune response and evolutionary adaptation

摘要 从全基因组关联研究中确定的大量疾病易感基因座是 使多基因风险评分(PR)能够兑现其改善健康结果和转变的承诺 个性化医疗的实践。常见病及相关疾病诊断报告质量下降 现代非洲人、亚洲人和美洲原住民祖先的数量性状相对于 然而，最近的欧洲祖先的种群有可能在 基于PRS的医疗服务的提供。具有基因组的非欧洲血统的个体数量 审问现在比5年前增长得快得多；然而， 最近的欧洲祖先对基因组的询问发展得更快，很可能需要很多年 在此之前，即使是主要大陆群体的基因组询问样本大小也接近于 相对人口规模。因此，在AS中优化不同人群的PRS性能是至关重要的 尽我们所能用很多方法。鉴于美国人口中携带基因组的比例很大，而且还在不断增长 混杂着来自不同大陆祖先的人，我们相信对于大部分美国人来说，高质量的PR 如果不适当考虑当地的祖先，就不太可能实现这一目标。同样，有重点的战略可以 识别高影响但特定于人群的变异可能会改善患有这种疾病的人群的PR质量 等位基因。来自具有自然选择特征的区域的DNA变体通常表现出这样的特性，并且 已被证明在许多血液学和血液学的顶级关联中富含 免疫/炎症特征是关键慢性病的重要生物标志物。我们建议集中我们的 血液学和免疫/炎症特征及其相关慢性病的PRS研究 扩展PR的开发方法以适应当地祖先的估计，影响很大 群体特有的变异和多种内表型。因此，我们的具体目标是：1)组装和 协调完成项目目标所需的数据集，包括血液学特征(RED 血细胞、白细胞、血小板)和免疫/炎症特征(C反应蛋白、纤维蛋白原、D-二聚体)，来自：Jackson 心脏研究、妇女健康倡议、BioVU和GeneSTAR。2)将PRS方法扩展为：a)显式 模范当地血统；b)适应大效应但特定于人群的风险等位基因(如 来自具有自然选择特征的区域)；以及c)允许对多个 内表型；以及3)开发和应用新的PRS和整体疾病预测模型：a) 评估常见疾病和相关生物标记物受血液病、血栓形成和 免疫/炎症生物学；以及b)能够计算经PRS调整的临床化验值以 缩小结构性健康差距。

Abstract The large number of disease susceptibility loci identified from genome-wide association studies (GWAS) is enabling polygenic risk scores (PRS) to deliver on their promise to improve health outcomes and to transform the practice of personalized medicine. The reduced quality of PRS for common diseases and related quantitative traits for populations of recent African, Asian, and Native American ancestries relative to those for populations of recent European ancestries, however, threatens to create a new class of disparities in the delivery of healthcare based on PRS. The number of individuals of non-European ancestry with genome interrogation are growing much more rapidly now than 5 years ago; nevertheless, the number of individuals of recent European ancestries with genome interrogation grows still more rapidly and it is likely to be many years before sample sizes for genome interrogation in even major continental groups are close to proportional to relative population sizes. Thus, it is critical to optimize PRS performance for diverse populations in as many ways as we can. Given the substantial and growing fraction of the US population with genomes admixed from different continental ancestries, we believe that high quality PRS for much of the US population is unlikely to be achieved without properly accounting for local ancestries. Similarly, focused strategies to identify high-impact but population-specific variants could improve the quality of PRS in populations with such alleles. DNA variants from regions with a signature of natural selection often demonstrate such properties, and have been shown to be enriched among top associations for a number of hematological and immune/inflammatory traits that are important biomarkers for key chronic diseases. We propose to focus our PRS studies on hematological and immune/inflammatory traits and their associated chronic diseases and to extend methods for the development of PRS to accommodate estimates of local ancestry, high impact population-specific variants and multiple endophenotypes. Thus, our Specific Aims are: 1) Assemble and harmonize data sets needed to accomplish the goals of the project, including hematological traits (red blood cell, white blood cell, platelet), and immune/inflammatory traits (CRP, fibrinogen, D-dimer) from: Jackson Heart Study, Women’s Health Initiative, BioVU, and GeneSTAR. 2) Extend PRS methods to: a) explicitly model local ancestry; b) accommodate large-effect but population-specific risk alleles (such as those from regions with a signature of natural selection); and c) enable joint modeling of multiple endophenotypes; and 3) Develop and apply novel PRS and overall disease prediction models to: a) estimate risk of common diseases and related biomarkers affected by hematological, thrombotic and immune/inflammatory biology; and b) enable calculation of PRS-adjusted clinical laboratory values to reduce structural health disparities.