Genomic Approaches to Population Health in Multi-Ethnic Hospital Systems

多民族医院系统中人口健康的基因组方法

• 批准号: 10264829
• 负责人: Valerie A Arboleda
• 金额: $ 76.86万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-16 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10264829
• 关键词: Address; Adoption; African American; Architecture; Asthma; Automobile Driving; Biological Markers; Categories; Chronic Disease; Clinical; Complex; Computerized Medical Record; Coupled; Data; Databases; Decision Making; Detection; Diabetes Mellitus; Diagnosis; Diagnostic; Discipline; Disease; Disease Outcome; Electronic Health Record; Engineering; Ensure; Ethnic group; European; Evaluation; Family history of; Fostering; Gene Frequency; Genetic; Genetic Databases; Genomic approach; Genomic medicine; Genomics; Genotype; Goals; Health; Health system; Healthcare; Healthcare Systems; Hospitals; Hypertension; Hypertrophic Cardiomyopathy; Individual; Institutes; Institution; International; Intervention; Investigation; Investments; Knowledge; Link; Measures; Medical; Medicine; Mendelian disorder; Methods; Modeling; Modernization; Monitor; Outcome; Pathogenicity; Patient Care; Patients; Pattern; Penetrance; Performance; Persons; Phenotype; Policy Making; Population; Population Genetics; Population Heterogeneity; Prevalence; Race; Rare Diseases; Research; Risk; Risk Assessment; Science; Statistical Methods; Stevens-Johnson Syndrome; System; Taiwan; Technology; Testing; Therapeutic; Translating; Translational Research; Variant; Work; base; biobank; burden of illness; clinical care; clinical database; clinical phenotype; clinical practice; clinical risk; cohort; disorder prevention; disorder risk; ethnic minority population; genetic information; genetic risk factor; genome-wide; genomic data; health care service utilization; health disparity; human disease; identity by descent; improved; multi-ethnic; new technology; novel; patient population; polygenic risk score; population based; population health; portability; precision medicine; racial and ethnic; rare genetic disorder; repository; success; tool; trait; whole genome

Project Summary Genomic medicine is a rapidly emerging medical discipline that incorporates the use of genomic information in patient care. Understanding an individual's genetic information holds the potential to improve diagnostic and therapeutic decision-making in clinical care, impact health outcomes and inform policy making. Yet the genomic datasets driving these decisions are often focused on populations of European descent. When these limited discoveries drive genomic medicine, understudied groups are frequently the last to benefit from advances in research, technology and clinical best practices. For true adoption, precision medicine needs to account for genomic diversity inherent to modern health systems. To address the importance of understanding disease risk in fine-scale populations present in modern health systems, and foster opportunities for advancement of genomic medicine in diverse populations, we have assembled a multi-ethnic cohort of over one million genotyped individuals from five international biobanks in health systems linked to electronic medical records. Leveraging this unique research cohort from our institutes, we will engineer fine-scale population detection and monitoring for population health powered by novel statistical and population genetics methods. These in turn can help us understand disease prevalence and refine our understanding of clinical variant pathogenicity. The systems we develop within hospitals will help characterize risk profiles for both rare (via Phenotype Scores) and common (via Polygenic Scores) traits, a necessary step to work in realistic, modern multi-ethnic hospital settings. These goals are implemented through three specific aims: Aim 1: Implement a monitoring system for differences in disease burden between fine-scale populations defined via identity-by-descent (IBD) inferred from genome-wide data across multiple biobanks. In so doing, we will apply a high-throughput, portable method to improve fine-scale ancestry and use it to improve disease and trait monitoring across multiple health systems. Aim 2: Improve our characterization of clinical variant pathogenicity, penetrance and expressivity via improved allele frequency examination through the fine-scale populations determined in Aim 1. Aim 3: Model risk via improved phenotype risk score (PheRS) for rare disease and polygenic risk score (PRS) for common traits across the fine-scale populations determined in Aim 1. We will develop improved trans- ethnic risk models and demonstrate their utility in improving our population-based understanding of disease outcomes. Our long-collaborating interdisciplinary team including clinical, statistical, and population geneticists has already produced preliminary data demonstrating not only a high likelihood of success, but also a desire and capacity to translate results into implemented changes in clinical care. This project will drive a new understanding of human disease, as well as opportunities for new health care interventions, particularly for currently understudied ethnic minority populations, thereby improving precision medicine for all.

项目摘要 基因组医学是一种快速新兴的医学学科，将基因组信息的使用纳入 病人护理。了解个人的遗传信息具有改善诊断和 临床护理，影响健康成果并提供政策制定的治疗决策。但是 推动这些决定的基因组数据集通常集中在欧洲血统的种群上。当这些 有限的发现驱动基因组医学，研究的群体通常是从中受益的最后一个 研究，技术和临床最佳实践的进步。为了进行真正的采用，精确医学需要 解释现代卫生系统固有的基因组多样性。 解决理解现代疾病风险的重要性的重要性 卫生系统，以及在不同人群中促进基因组医学发展的机会，我们有 组建了来自五个国际生物库的一百万个基因分型个体的多种族队列 与电子病历相关的卫生系统。利用我们学院的这一独特的研究队列 我们将设计由新颖的人口卫生的细数人口检测和监测 统计和种群遗传学方法。这些反过来可以帮助我们了解疾病的患病率和 完善我们对临床变异致病性的理解。我们在医院内开发的系统将有所帮助 表征了稀有（通过表型得分）和常见（通过多基因得分）特征的风险特征，A 在现实的多民族医院环境中工作的必要步骤。这些目标已实施 通过三个具体目标： AIM 1：实施监测系统，以解决高规模人群之间疾病负担的差异 通过从多个生物库中从全基因组数据中推断出的逐种性（IBD）定义。这样，我们 将采用高通量，便携式方法来改善精细的血统，并使用它来改善疾病和 跨多个卫生系统监测特征。 目标2：改善我们通过改善的临床变异性致病性，外观和表现性的表征 通过在AIM 1中确定的高尺度种群的等位基因频率检查。 AIM 3：通过改进的稀有疾病和多基因风险评分（PRS）改善表型风险评分（PHS）的模型风险 对于在AIM 1中确定的精细种群中的常见特征。 种族风险模型，并证明了他们在改善我们基于人群的疾病理解方面的效用 结果。 我们的长期跨学科团队，包括临床，统计和人口遗传学家 已经产生了初步数据，不仅证明了成功的可能性很高，而且还表明了欲望和 将结果转化为实施临床护理变化的能力。这个项目将推动一个新的 了解人类疾病以及新的医疗干预措施的机会，特别是 目前正在研究的少数民族人口，从而改善了所有人的精确医学。