Vanderbilt Genome-Electronic Records (VGER) Project

范德比尔特基因组电子记录 (VGER) 项目

• 批准号: 10659136
• 负责人: DAN M RODEN
• 金额: $ 136.74万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 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/10659136
• 关键词: Academic Medical Centers; Address; Assessment tool; Bioethics; Biological Markers; Biomedical Research; Caring; Chronic Kidney Failure; Clinical; Clinical Medicine; Colorectal Cancer; 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; Electronics; Family; Family health status; Focus Groups; Future; Genome; Genomic medicine; Genomics; Goals; Growth; Health; Health Personnel; Healthcare; Heritability; Human; Individual; Informatics; Information Sciences; Intervention; Knowledge; Learning; 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; Productivity; 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

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 易感性、表现、进展和治疗反应。现代大数据分析表明，大多数 我们中的大多数人对大多数疾病具有“平均”易感性，但我们每个人对少数疾病的风险很高。这一发现提供了 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 治疗。我们在此提出一项计划，该计划建立在关键赋能领域十多年的发展和知识的基础上 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，以及自网络成立以来作为 eMERGE 富有成效的参与者的经验。具体来说 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 疾病。基因组风险评估将纳入多基因风险评分、家族健康史和 临床疾病预测因子。我们建议 eMERGEgram 指导委员会选择以下疾病： 遗传;显示不同血统的不同影响；与可用的早期检测、预防或 治疗干预；其中大型多祖先基因组范围关联研究可用于 制定多基因风险评分。使用这些标准，我们提供的数据支持对冠状动脉的关注 疾病、慢性肾病、2型糖尿病、子宫肌瘤和结直肠癌。在具体目标 2 中，我们 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 生物医学研究），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；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 协调中心。在具体目标 3 中，我们将利用 eMERGEgram 经验来提高我们的能力： 提供基因组风险评估。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 人群和亚组内。我们将在我们的数据库中使用超过 100,000 条记录的共享 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。额外的研究目标将是 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。