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

摘要 全基因组关联研究 (GWAS) 确定的大量疾病易感位点 使多基因风险评分 (PRS) 能够兑现改善健康结果和转变的承诺 个性化医疗的实践。常见疾病及相关疾病的 PRS 质量下降 近代非洲、亚洲和美洲原住民血统的人口相对于 然而，近代欧洲血统的人口有可能在社会中造成新的不平等阶层。 基于 PRS 的医疗保健服务。具有基因组的非欧洲血统个体的数量 与 5 年前相比，现在审讯的增长速度要快得多；尽管如此， 最近经过基因组审讯的欧洲血统增长得更快，而且可能需要很多年 在即使是主要大陆群体的基因组调查样本量也接近成正比之前 相对人口规模。因此，优化不同人群的 PRS 性能至关重要。 我们可以采取多种方式。鉴于拥有基因组的美国人口比例相当大且不断增长 我们相信，来自不同大陆血统的高质量 PRS 适合大多数美国人口 如果不适当考虑当地血统，就不可能实现这一目标。同样，重点战略 识别高影响力但针对特定人群的变异可以提高具有此类人群的 PRS 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 免疫/炎症特征是关键慢性疾病的重要生物标志物。我们建议将重点放在 关于血液学和免疫/炎症特征及其相关慢性疾病的 PRS 研究 扩展 PRS 的开发方法，以适应对当地血统、高影响力的估计 人群特异性变异和多种内表型。因此，我们的具体目标是： 1) 组装和 协调实现项目目标所需的数据集，包括血液学特征（红色 血细胞、白细胞、血小板）和免疫/炎症特征（CRP、纤维蛋白原、D-二聚体）来自：Jackson 心脏研究、女性健康倡议、BioVU 和 GeneSTAR。 2) 将 PRS 方法扩展为： a) 显式地 当地血统的模范； b) 适应大效应但人群特异性的风险等位基因（例如那些 来自具有自然选择特征的地区）； c) 实现多个联合建模 内表型； 3) 开发并应用新型 PRS 和整体疾病预测模型： 估计常见疾病的风险以及受血液、血栓和疾病影响的相关生物标志物 免疫/炎症生物学； b) 能够计算 PRS 调整后的临床实验室值 减少结构性健康差距。

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.