Elucidating the ancestry-specific genetic and environmental architecture of cardiometabolic traits across All of Us ethnic groups

阐明我们所有种族群体心脏代谢特征的祖先特异性遗传和环境结构

• 批准号: 10796028
• 负责人: JEFFREY R O'CONNELL
• 金额: $ 19.31万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-10 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10796028
• 关键词: APOL1 gene; Accounting; Address; Adoption; African American population; Age; Algorithms; Alleles; Architecture; Biological; Blood Pressure; Body mass index; Cardiovascular Diseases; Communities; Complex; Computer software; Data; Data Set; Disease; Disparity; Early Intervention; Educational Activities; Environment; Environmental Exposure; Environmental Risk Factor; Ethnic Origin; Ethnic Population; Evolution; Functional disorder; Gender; Genes; Genetic; Genetic Variation; Genotype; Glucose; Goals; Heritability; Instruction; Investigation; Kidney Diseases; Learning; Lipids; Manuals; Modeling; Physical activity; Population; Prevalence; Prevention; Reliability of Results; Research; Research Personnel; Resources; Risk; Running; Sexual and Gender Minorities; Shapes; Smoking; Software Tools; Source; Testing; Therapeutic; Training; Treatment Factor; burden of illness; cardiometabolism; clinical phenotype; cohort; disease disparity; ethnic minority; gene environment interaction; genome wide association study; genome-wide; genome-wide analysis; health disparity; healthspan; human disease; insight; lifestyle factors; non-diabetic; precision medicine; racial minority; rural area; sex; social determinants; tool; trait; urban area; whole genome

PROJECT SUMMARY/ABSTRACT All of Us represents a unique resource to understand the genetic, environmental, and social determinants of complex traits across the broad diverse US population. All of Us encompasses underrepresented sexual and gender, racial and ethnic minorities, living in urban and rural areas. Currently whole-genome sequence data (WGS) is available on close to 100,000 subjects with 250,000 subjects expected by summer. Human disease is a complex interplay between both genes and environment. A better understanding of how disease is modified by genetic interactions with environmental, lifestyle and treatment factors as well as age, sex, and ancestry, will provide insights into prevention, early intervention, and potential therapeutic strategies to reduce the burden of disease and health disparities. Cardiometabolic traits such a BMI, glucose levels, lipid levels, blood pressure are important determinants cardiovascular disease. Understanding the genetic and environmental differences between ethnic groups is an essential component to understanding disease prevalence. We know traits can have different heritability across ethnic groups, shaped by thousands of years of independent evolution. This evolution is seen in the All of US WGS where ~12% of the markers are multi-allelic, thus, representing different alternate alleles that arose in different populations, each with a potentially different biological effect. To be able to understand how the genetic and environmental architecture of complex traits differs between All of Us ethnic groups we need workflows in the Researcher Workbench that can model diverse sources of genetic variation from variance component models to genome-wide association with and without environmental interactions. To achieve this understanding, we propose three aims. In Aim 1 we develop models that can incorporate multiple traits, multiple exposures, and multiple ethnic strata to be able to quantify the trait genetic and environmental architecture within and between ethnic groups. In Aim 2 we develop and implement rigorously tested workflows for the tools developed in Aim 1 into the All of Us Researcher Workbench. The workflows will be supported by with extensive training materials that will include video tutorials, user manuals, and example data sets and instructions how to analyze them. In Aim 3 we apply our All of Us Researcher Workbench workflows to investigate the genetic and environmental architecture of cardiometabolic traits across All of Us ethnic groups. These traits will include lipids, glucose, blood pressure and BMI. Environmental exposures will include smoking, education, and physical activity. Our Researcher Workbench workflows will enable researchers to apply the same models to the extensive list of clinical phenotypes and exposures available in All of Us to address sources of important health disparities.

项目总结/摘要 我们所有人代表了一个独特的资源，以了解遗传，环境和社会的决定因素， 复杂的特征在广泛多样的美国人口。我们所有人都包括代表性不足的性和 生活在城市和农村地区的性别、种族和族裔少数群体。目前全基因组序列数据 (WGS)可用于近10万名受试者，预计到夏季将有25万名受试者。 人类疾病是基因和环境之间复杂的相互作用。更好地了解如何 疾病通过与环境、生活方式和治疗因素以及年龄的遗传相互作用而改变， 性别和血统，将提供深入了解预防，早期干预，和潜在的治疗策略， 减少疾病负担和健康差距。 心脏代谢特征，如体重指数，血糖水平，血脂水平，血压是重要的决定因素 心血管疾病了解种族群体之间的遗传和环境差异是一个 了解疾病流行的重要组成部分。我们知道性状的遗传性 跨越了数千年的独立进化所形成的种族群体。这种演变在所有的 其中约12%的标记是多等位基因的，因此，代表不同的替代等位基因， 在不同的人群中出现，每种都有潜在的不同生物效应。 为了能够理解复杂性状的遗传和环境结构在所有人之间的差异， 我们的种族群体，我们需要在研究人员的工作流程，可以模拟不同的来源， 从方差分量模型到全基因组关联的遗传变异，有和没有环境 交互.为了实现这一目标，我们提出了三个目标。 在目标1中，我们开发了可以整合多种特征，多种暴露和多个种族阶层的模型 能够量化种族群体内部和之间的遗传和环境结构。 在目标2中，我们为目标1中开发的工具开发并实施了经过严格测试的工作流程， 美国研究员。这些工作流程将得到广泛的培训材料的支持， 包括视频教程、用户手册和示例数据集以及如何分析它们说明。 在目标3中，我们应用我们所有研究人员的工作流程来调查遗传和环境 我们所有种族群体的心脏代谢特征的结构。这些性状包括脂质，葡萄糖， 血压和BMI。环境暴露包括吸烟、教育和体力活动。 我们的研究人员工作流程将使研究人员能够将相同的模型应用于广泛的列表 临床表型和暴露在我们所有人中，以解决重要的健康差异的来源。