Genetic & Social Determinants of Health: Center for Admixture Science and Technology

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基本信息

批准号：
10818088
负责人：
KELLY A FRAZER
金额：
$ 192.87万
依托单位：
YALE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-07-01 至 2026-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10818088
关键词：
Admixture Affect African Algorithms All of Us Research Program American American Indians Asian population Awareness Behavior Benchmarking Biology Cardiovascular Diseases Cardiovascular system Categories Characteristics Clinical Complex Data Diagnosis Disease model Electronic Health Record Environment Ethnic Origin Ethnic Population European Exclusion Genes Genetic Genetic Determinism Genetic Variation Genome Genomic medicine Genomics Goals Health Health Surveys Healthcare Heart Incidental Findings Individual Intervention Joints Language Major Histocompatibility Complex Malignant Neoplasms Maps Medical Medical Genetics Methods Minority Minority Groups Modeling Morbidity - disease rate Native Americans Natural Language Processing Outcome Participant Pathogenicity Persons Phenotype Policies Population Population Heterogeneity Poverty Prognosis Publishing Race Recommendation Reporting Research Research Personnel Risk Science Single Nucleotide Polymorphism Site Social Adjustment Socioeconomic Factors Socioeconomic Status Source Tandem Repeat Sequences Techniques Technology United States Variant Veterans algorithm development cardiometabolism cluster computing cohort data privacy data sharing design ethnic minority population follow-up genetic information genome sciences genome wide association study health determinants health disparity health economics health outcome disparity improved innovation large datasets medical schools mortality novel novel strategies polygenic risk score poor health outcome prevent privacy protection programs prospective racial minority racial population repository risk prediction social determinants social factors social health determinants socioeconomics statistics tool trait

项目摘要

PROJECT SUMMARY It is imperative to understand the underlying sources of the large health disparities among individuals from different racial and ethnic groups living in the United States (US). Complex relationships between genetics and social factors influence health outcomes. Approximately 33% of people in the US belong to an ethnic minority group and ~12.5% live below the federal poverty line. Historical and recent mixing of Europeans, Native Americans, Africans and Asians resulted in the US population having a relatively large number of admixed individuals who carry ancestry from outside their self-identified race. The All of Us (AoU) Program and the Million Veterans Program (MVP) include genetic, health and socioeconomic information on all participants, and therefore provide an opportunity to identify factors contributing to health disparities. However, the AoU program and MVP require their data to stay within local hosting sites, therefore conducting joint analyses on these cohorts requires the development of algorithms that enable privacy-protecting distributed computing (i.e., without revealing individual-level data). There are three important gaps in understanding genetic determinants of health: 1) most studies have been dominated by European individuals, and while they control for global ancestry, there is no attempt to model the patchwork of local ancestry characteristic of admixed individuals; 2) GWAS are primarily conducted using SNPs, while important sources of ancestry-specific genetic variation (tandem repeats (TRs) and the major histocompatibility complex (MHC) interval) are not assayed; and 3) most GWAS do not adjust for socioeconomic factors. The American College of Medical Genetics and Genomics (ACMG) has published a list of medically actionable cancer and cardiovascular genes recommended for return of incidental findings of pathogenic variants to reduce morbidity and mortality, but having minorities excluded from healthcare follow up due to common barriers (e.g., language and access) makes it difficult to distinguish between the genetic and socioeconomic factors that contribute to disparate health outcomes. The goal of the CAST (Center for Admixture Science and Technology) program is to improve the clinical utility of genetic information for all populations living in the US. In Aim 1, we will develop and apply multivariate models of disease risk prediction that incorporate local ancestry, complex variants (TRs and HLA types). In Aim 2, we will conduct scalable distributed computing using data from millions of individuals across the AoU and MVP compute enclaves. In Aim 3, we will develop new approaches to characterize phenotypes using electronic health records and surveys from AoU and MVP, assess the impact of including social determinants of health in our models, and prospectively evaluate them with new AoU and MVP participants. To achieve these goals, we assembled a highly interdisciplinary group of researchers with expertise in Genetics, Genome Biology, Data Sharing Policy and Technology, Health Disparities, Phenotyping, and Statistics.

项目概要必须了解不同种族之间巨大健康差异的根本原因居住在美国 (US) 的不同种族和族裔群体。遗传与基因之间的复杂关系社会因素影响健康结果。大约 33% 的美国人属于少数族裔约 12.5% 的人生活在联邦贫困线以下。历史上和近代欧洲人、本土人的混合美国人、非洲人和亚洲人导致美国人口中混血数量较多具有来自其自我认定的种族之外的血统的个人。我们所有人 (AoU) 计划和百万退伍军人计划 (MVP) 包括所有参与者的遗传、健康和社会经济信息，以及因此，提供了一个机会来确定造成健康差异的因素。然而，AoU 计划和 MVP 要求他们的数据保留在本地托管站点内，因此对这些群体进行联合分析需要开发能够保护隐私的分布式计算的算法（即，无需揭示个人层面的数据）。在理解健康的遗传决定因素方面存在三个重要差距： 1）大多数研究都是以欧洲个体为主，虽然他们控制了全球血统，但并不是试图模拟混合个体的当地血统特征的拼凑； 2) GWAS 是主要使用 SNP 进行，而祖先特异性遗传变异的重要来源（串联重复序列）（TR）和主要组织相容性复合物（MHC）间隔）未进行测定； 3) 大多数 GWAS 不调整社会经济因素。美国医学遗传学与基因组学院 (ACMG) 发表了一份可医学上采取行动的癌症和心血管基因列表，建议返回意外事件致病变异的发现可降低发病率和死亡率，但将少数群体排除在医疗保健之外由于共同的障碍（例如语言和访问），后续工作很难区分遗传因素以及导致不同健康结果的社会经济因素。 CAST（中心）的目标混合物科学与技术）计划旨在提高遗传信息对所有人的临床效用居住在美国的人口。在目标 1 中，我们将开发并应用疾病风险预测的多变量模型融合了当地血统、复杂变异（TR 和 HLA 类型）。在目标 2 中，我们将开展可扩展的使用 AoU 和 MVP 计算飞地中数百万个人的数据进行分布式计算。瞄准 3、我们将开发新的方法来利用电子健康记录和调查来表征表型 AoU 和 MVP，评估将健康的社会决定因素纳入我们的模型的影响，并前瞻性地与新的 AoU 和 MVP 参与者一起评估他们。为了实现这些目标，我们组建了一支高度由在遗传学、基因组生物学、数据共享政策和技术、健康差异、表型分析和统计。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

sfkit: a web-based toolkit for secure and federated genomic analysis.

DOI：
10.1093/nar/gkad464
发表时间：
2023-07-05
期刊：
Nucleic acids research
影响因子：
14.9
作者：
通讯作者：

Polymorphic short tandem repeats make widespread contributions to blood and serum traits.

DOI：
10.1016/j.xgen.2023.100458
发表时间：
2023-12-13
期刊：
CELL GENOMICS
影响因子：
0
作者：
Margoliash, Jonathan;Fuchs, Shai;Li, Yang;Zhang, Xuan;Massarat, Arya;Goren, Alon;Gymrek, Melissa
通讯作者：
Gymrek, Melissa

HMOX1 Genetic Polymorphisms Display Ancestral Diversity and May Be Linked to Hypertensive Disorders in Pregnancy.

DOI：
10.1007/s43032-022-01001-1
发表时间：
2022-12
期刊：
Reproductive sciences (Thousand Oaks, Calif.)
影响因子：
0
作者：
通讯作者：

Assessing transcriptomic reidentification risks using discriminative sequence models.

DOI：
10.1101/gr.277699.123
发表时间：
2023-07
期刊：
GENOME RESEARCH
影响因子：
7
作者：
Sadhuka, Shuvom;Fridman, Daniel;Berger, Bonnie;Cho, Hyunghoon
通讯作者：
Cho, Hyunghoon

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues.

DOI：
10.1016/j.celrep.2021.110020
发表时间：
2021-11-16
期刊：
Cell reports
影响因子：
8.8
作者：
D'Antonio M;Nguyen JP;Arthur TD;Matsui H;COVID-19 Host Genetics Initiative;D'Antonio-Chronowska A;Frazer KA
通讯作者：
Frazer KA