Vanderbilt Genome-Electronic Records (VGER) Project

范德比尔特基因组电子记录 (VGER) 项目

基本信息

批准号：
10450009
负责人：
DAN M RODEN
金额：
$ 144.81万
依托单位：
VANDERBILT UNIVERSITY MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-01 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10450009
关键词：
Academic Medical Centers Address Assessment tool Bioethics Biological Markers Biomedical Research Caring Chronic Kidney Failure Clinical Clinical Medicine Colorectal Cancer Communities Computerized Medical Record Coronary Arteriosclerosis Coupled DNA Data Data Analytics Data Set Detection Development Discipline Disease Disease Progression Disease susceptibility Early Diagnosis Early identification Early treatment Electronic Health Record Electronic Medical Records and Genomics Network Family Family health status Focus Groups Foundations Future Genome Genomic medicine Genomics Goals Growth Health Health Personnel Healthcare Heritability Human Individual Informatics Information Sciences Intervention Knowledge Link Maps Methods Modeling Modernization National Center for Advancing Translational Sciences Non-Insulin-Dependent Diabetes Mellitus Outcome Study Participant Pathogenicity Patients Persons Pharmaceutical Preparations Pharmacogenomics Phenotype Physiological Population Predisposition Prevention Prevention approach Provider Recording of previous events Records Research Resources Risk Risk Assessment Risk Management Sampling Science Site Strategic vision Subgroup Testing Underrepresented Populations United States National Institutes of Health Uterine Fibroids Validation Variant analytical method biobank care outcomes clinical decision support clinical phenotype cohort community engagement disorder risk experience genetic pedigree genetic variant genome wide association study health care service utilization high risk human old age (65+)improved innovation large datasets meetings novel patient engagement personalized approach personalized care phenome polygenic risk score precision medicine programs recruit response tool trait treatment response uptake

项目摘要

The concept of Precision Medicine builds on the age-old understanding that humans vary in their disease susceptibility, presentation, progression, and therapeutic response. Modern large data analytics reveal that most of us have “average” susceptibility for most diseases, but each of us has high risk for a few. This finding provides the opportunity and challenge – addressed by this eMERGE Genomic Risk Assessment and Management (eMERGEgram) initiative – to identify people at high risk for common diseases to promote prevention or early treatment. We propose here a program that builds on over a decade of growth and knowledge in key enabling disciplines including informatics, genomics, bioethics, participant and community engagement, and clinical medicine, and of experience as productive participants in eMERGE since the network's inception. In Specific Aim 1, we will develop and validate Genomic Risk Assessment tools to identify people at high risk for common diseases. The Genomic Risk Assessments will incorporate polygenic risk scores, family health history, and clinical disease predictors. We propose that the eMERGEgram Steering Committee select diseases that are heritable; display variable impact across ancestries; are associated with available early detection, prevention or treatment interventions; and in which large multi-ancestry genome wide association studies are available to develop polygenic risk scores. Using these criteria, we present data that support a focus on coronary artery disease, chronic kidney disease, type 2 diabetes, uterine fibroids, and colorectal cancer. In Specific Aim 2, we will build on experience in eMERGE-3, All of Us, and our NIH-supported Recruitment Innovation Center to execute a program that will engage, recruit, and retain 2,500 subjects (>35% from populations under-represented in biomedical research), including family dyads or trios. We will compute Genomic Risk Assessments for network- selected target conditions; return results to participants, their healthcare providers, and their electronic health records; and track healthcare outcomes including disease detection or healthcare utilization and deliver these to the Coordinating Center. In Specific Aim 3, we will use the eMERGEgram experience to improve our ability to deliver Genomic Risk Assessment. We will assess the uptake and impact of Genomic Risk Assessments and the extent to which the components of the Genomic Risk Assessment provide independent information across populations and within subgroups. We will use a shared DNA segment map across >100,000 records in our biobank to develop the concept of a genetically-informed family history, a tool that can inform health risk in the absence of a large pedigree, as is the case for small or adoptive families. Additional research goals will be driven by participants, developed through community engagement by focus groups in Years 1-2 and highly intentional participant interaction throughout the project.

精准医学的概念建立在人类疾病差异这一古老的认识之上现代大数据分析揭示了大多数情况。我们中的大多数人对大多数疾病具有“平均”易感性，但我们每个人对某些疾病的风险很高。这一发现表明。 eMERGE 基因组风险评估和管理解决了机遇和挑战 (eMERGEgram) 倡议 – 识别常见疾病的高风险人群，以促进预防或早期预防我们在此提出一项基于十多年来关键支持方面的发展和知识的计划。学科包括信息学、基因组学、生物伦理学、参与者和社区参与以及临床医学，以及自 eMERGE 网络成立以来作为富有成效的参与者的经验。目标 1，我们将开发和验证基因组风险评估工具，以识别常见疾病高风险人群基因组风险评估将纳入多基因风险评分、家族健康史和我们建议 eMERGEgram 指导委员会选择以下疾病：可遗传；显示出不同血统的影响；与现有的早期检测、预防或治疗有关；治疗干预措施；以及大型多祖先全基因组关联研究使用这些标准制定多基因风险评分，我们提供支持关注冠状动脉的数据。在具体目标 2 中，我们针对疾病、慢性肾病、2 型糖尿病、子宫肌瘤和结直肠癌进行了研究。将借鉴 eMERGE-3、All of Us 和 NIH 支持的招聘创新中心的经验，执行一项计划，将吸引、招募和留住 2,500 名受试者（> 35% 来自代表性不足的人群在生物医学研究中），包括家庭二人组或三人组，我们将计算网络的基因组风险评估。选定的目标条件；将结果返回给参与者、他们的医疗保健提供者和他们的电子健康记录；并跟踪医疗保健结果，包括疾病检测或医疗保健利用，并将这些结果交付给在具体目标 3 中，我们将利用 eMERGEgram 经验来提高我们的能力：我们将评估基因组风险评估的采用和影响。基因组风险评估的各个组成部分提供独立信息的程度我们将在我们的超过 100,000 条记录中使用共享 DNA 片段图。生物银行开发了遗传信息家族史的概念，这是一种可以告知健康风险的工具缺乏大的血统，就像小家庭或收养家庭的情况一样，还会有额外的研究目标。由参与者驱动，通过第一年至第二年焦点小组的社区参与而发展，并且高度整个项目中有意的参与者互动。