PRS Center for Admixed Populations and Health Equity (CAPE)

PRS 混合人口和健康公平中心 (CAPE)

• 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
• 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

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.

项目总结/摘要 多基因风险评分（PRS），即基因组中常见变异的风险汇总，已成为一种新的风险评估方法。 这是实现基因组医学的有力工具。不幸的是，绝大多数来自 据估计，目前的PRS来自欧洲血统的个人，因此禁止 对非欧洲人实施减贫战略。为了解决这一差距，多个大规模的基因组 目前的研究是在非欧洲人中进行的。特别感兴趣的是最近 来自多个大陆来源的祖先，如非洲裔美国人和/或西班牙裔美国人， 基因组是不同祖先片段的镶嵌体。这种遗传祖先的多样性， 由于现有PRS的准确性和偏差在基因组之间存在差异，因此公平PRS开发面临挑战 祖先不像现有的范式，在很大程度上认为遗传祖先作为一个混杂因素，在PRS研究，我们 目的是充分整合混合过程的群体遗传学，以产生提供 公平的准确性，所有个人，无论遗传祖先。我们将整合超过23万的数据 混合了五个不同医疗系统的个人，包括加州大学洛杉矶分校、西奈山、科罗拉多， 为混合个体校准和基准PRS。

项目成果

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
• 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。

• DOI: 10.1101/2023.05.16.541036
• 发表时间: 2023
• 期刊: bioRxiv : the preprint server for biology
• 作者: Dang,Meihua;Liu,Anji;Wei,Xinzhu;Sankararaman,Sriram;VandenBroeck,Guy
• 通讯作者: VandenBroeck,Guy