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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

基本信息

批准号：
10212768
负责人：
Nancy J Cox
金额：
$ 99.99万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
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/10212768
关键词：
APOL1 gene Accounting Affect African American Alleles Asian Americans Asians Biological Assay Biological Markers Biology Blood Cells Blood Platelets C-reactive protein Calibration Chronic Chronic Disease Clinical Communicable Diseases DNA Data Data Set Diagnosis Disease Disease Pathway Disease Progression Disease susceptibility Erythrocytes European Fibrin fragment D Fibrinogen Frequencies Gene Frequency Genetic Variation Genome Genotype Goals Health Healthcare Hematology Heritability Hispanics Immune Immune response Individual Inflammation Inflammatory Jackson Heart Study Joints Kidney Laboratories Latino Lead 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 Property Research Methodology Risk Estimate Role Sample Size Scoring Method Sickle Cell Anemia Sickle Hemoglobin Site Structure Susceptibility Gene Testing Variant Weight White Blood Cell Count procedure Women&apos s Health base chemokine receptor clinical biomarkers clinical care cohort data harmonization diagnostic accuracy disorder risk endophenotype genetic variant genome wide association study 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

项目摘要

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.

摘要