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

多基因风险评分和健康差异：血细胞免疫反应和进化适应的作用

• 批准号: 10613573
• 负责人: Nancy J Cox
• 金额: $ 99.81万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-08 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10613573
• 关键词: APOL1 gene; Accounting; Affect; African American; African American population; Alleles; Asian Americans; Asian population; Biological Assay; Biological Markers; Biology; Blood Cells; Blood Platelets; C-reactive protein; Calibration; Chronic Disease; Chronic Kidney Failure; Clinical; Communicable Diseases; DNA; Data; Data Set; Diagnosis; Disease; Disease Pathway; Disease Progression; Disease susceptibility; Disparity; Erythrocytes; European; European ancestry; Fibrin fragment D; Fibrinogen; Frequencies; Gene Frequency; Genetic Variation; Genome; Genotype; Goals; Health; Healthcare; Hematology; Heritability; Hispanic; Immune; Immune response; Individual; Inflammation; Inflammatory; Jackson Heart Study; Joints; Laboratories; Latino; Leukocytes; Linkage Disequilibrium; Measures; Mendelian disorder; Modeling; Monitor; Mutation; Native American Ancestry; Natural Selections; Outcome; Pathway interactions; Performance; Phenotype; Population; Population Genetics; Population Heterogeneity; Population Sizes; Predisposition; Property; Research Methodology; Risk Estimate; Role; Sample Size; Scoring Method; Sickle Cell Anemia; Sickle Hemoglobin; Site; Susceptibility Gene; Testing; Variant; Weight; White Blood Cell Count procedure; Women' s Health; chemokine receptor; clinical biomarkers; clinical care; cohort; data harmonization; diagnostic accuracy; disorder risk; endophenotype; genetic variant; genome wide association study; genome-wide analysis; health care delivery; health care service utilization; health disparity; human disease; improved; in silico; inter-individual variation; lifetime risk; method development; novel; pathogen; personalized medicine; phenotypic data; polygenic risk score; predictive modeling; pressure; risk variant; thrombotic; trait

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.

抽象的 从全基因组关联研究（GWAS）中定位的大量疾病易感性是 使多基因风险评分（PRS）能够兑现他们的诺言，以改善健康结果并转变 个性化医学的实践。普通疾病和相关疾病的PR质量降低 最近的非洲，亚洲和美国原住民祖先相对于近代人的种群的定量特征 然而，最近的欧洲祖先人群威胁要在 基于PRS提供医疗保健。具有基因组的非欧洲血统的个体人数 现在的审讯比5年前的审讯速度更快。然而， 最近有基因组审查的欧洲祖先的增长越来越快，很可能已经很多年了 甚至在主要大陆群中的基因组询问样本量之前， 相对人口规模。这是至关重要的 尽可能多的方式。鉴于美国人口的大量和增长的基因组 我们认为来自不同大陆祖先的混合，我们认为美国大部分人口的高质量PR 如果没有适当考虑当地祖先，就不可能实现。同样，集中的策略 识别高影响但特定人群的变体可以提高此类人群中的PR质量 等位基因。具有自然选择签名区域的DNA变体通常表现出这种特性，并且 已显示出许多血液学和 免疫/炎症性状是关键慢性疾病的重要生物标志物。我们建议集中精力 关于血液学和免疫/炎症性状及其相关慢性疾病的PRS研究 扩展开发PR的方法，以适应当地血统的估计，高影响力 人群特定的变体和多种内型型。那就是我们的具体目的是：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（红色） 血细胞，白细胞，血小板）和免疫/炎症性状（CRP，纤维蛋白原，D-二聚体）来自：杰克逊 心脏研究，妇女健康计划，BIOVU和GENESTAR。 2）将PRS方法扩展到：a）明确 模型当地血统； b）容纳大型但人口特定的风险等位基因（例如 来自具有自然选择签名的地区）； c）启用多个的联合建模 内型型； 3）开发和应用新颖的PR和总体疾病预测模型为：a） 估计受血液学，血栓形成和血液学影响的常见疾病和相关生物标志物的风险 免疫/炎症生物学； b）能够计算PRS调整后的临床实验室值 减少结构性健康分布。