PRS Center for Admixed Populations and Health Equity (CAPE)

PRS 混合人口和健康公平中心 (CAPE)

基本信息

批准号：
10618377
负责人：
Eimear Elizabeth Kenny
金额：
$ 96.8万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
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/10618377
关键词：
Acceleration Address Admixture African American population African ancestry Americas Asian ancestry Awareness Benchmarking Calibration Clinical Data Cohort Studies Colorado Complex Data Data Set Databases Development Disease East Asian Electronic Health Record Environmental Risk Factor Epidemiology Equity Ethnic Origin European European ancestry Event Gene Expression Genetic Genetic Determinism Genetic Drift Genetic Models Genetic Variation Genetic study Genome Genomic medicine Genomics Genotype Health system Heterogeneity Hispanic Americans Human Incidence Individual Jackson Heart Study Link Location Longitudinal cohort Maps Medical Medicine Methods Mexican Americans Modeling Molecular Participant Patient Self-Report Population Population Genetics Process Proxy Puerto Rican Race Relative Risks Research Risk Risk Factors Sample Size Slave Socioeconomic Status Source Statistical Methods Structure System Testing Uncertainty Variant World Health biobank causal variant cohort data harmonization data integration digital health disease natural history empowerment genetic architecture genome-wide genomic data health data health equity health management improved interest migration mosaic novel patient population phenotypic data polygenic risk score population based portability pressure social health determinants tool trait transcriptome urban setting

项目摘要

Project Summary/Abstract Polygenic risk scores (PRS), that aggregate risk across common variants in the genome, have emerged as a powerful tool towards implementing genomic medicine. Unfortunately, the vast majority of genomic data from which current PRS are estimated is coming from European ancestry individuals thus prohibiting the implementation of PRS for non-European individuals. To address this gap, multiple large-scale genomic studies are currently performed in non-European individuals. Of particular interest are individuals with recent ancestry from multiple continental sources such as African Americans and/or Hispanic Americans whose genomes are a mosaic of segments of various ancestries. Such diversity in genetic ancestry raises unique challenges in the equitable PRS development as the accuracy and bias of existing PRS varies across genomic ancestries. Unlike existing paradigm that largely views genetic ancestry as a confounder in PRS studies, we aim to fully integrate population genetics of the admixture process to yield admixture-PRS that provide equitable accuracies for all individuals irrespective of genetic ancestries. We will integrate data of over 230,000 admixed individuals across five diverse medical systems including UCLA, Mt Sinai, Colorado to develop, calibrate and benchmark PRS for admixed individuals.

项目摘要/摘要多基因风险评分（PRS）是基因组中常见变体的总风险的多基因风险评分，已成为一个实施基因组医学的强大工具。不幸的是，绝大多数的基因组数据来自当前的PR估计来自欧洲血统，因此禁止实施非欧洲人的PR。为了解决这一差距，多个大型基因组目前在非欧洲个体进行研究。特别感兴趣的人是最近来自多个大陆来源的祖先，例如非裔美国人和/或西班牙裔美国人基因组是各种祖先段的镶嵌物。遗传血统的这种多样性提高了独特的随着现有PR的准确性和偏差在基因组中的准确性和偏见随着基因组而有所不同祖先。与现有的范式不同，在很大程度上将遗传血统视为PRS研究中的混杂因素，我们旨在完全整合混合过程的人口遗传学，以产生提供的混合物PRS 无论遗传祖先如何，所有个体的公平精度。我们将整合超过230,000的数据在五种不同的医疗系统中的混合个人，包括加州大学洛杉矶分校，西奈山，科罗拉多州，开发，用于混合个体的校准和基准PR。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Accounting for isoform expression increases power to identify genetic regulation of gene expression.

考虑同种型表达增加了识别基因表达的遗传调控的能力。

DOI：
10.1371/journal.pcbi.1011857
发表时间：
2024
期刊：
PLoS computational biology
影响因子：
4.3
作者：
LaPierre,Nathan;Pimentel,Harold
通讯作者：
Pimentel,Harold

Admix-kit: An Integrated Toolkit and Pipeline for Genetic Analyses of Admixed Populations.

Admix-kit：用于混合群体遗传分析的集成工具包和管道。

DOI：
10.1101/2023.09.30.560263
发表时间：
2023
期刊：
bioRxiv : the preprint server for biology
影响因子：
0
作者：
Hou,Kangcheng;Gogarten,Stephanie;Kim,Joohyun;Hua,Xing;Dias,Julie-Alexia;Sun,Quan;Wang,Ying;Tan,Taotao;PolygenicRiskMethodsinDiversePopulations(PRIMED)ConsortiumMethodsWorkingGroup;Atkinson,ElizabethG;Martin,Alicia;Shortt,J
通讯作者：
Shortt,J

Tractable and Expressive Generative Models of Genetic Variation Data.

遗传变异数据的易处理且富有表现力的生成模型。