Vanderbilt Genome-Electronic Records (VGER) Project

精准医学的概念建立在一个由来已久的认识上，即人类的疾病是不同的 敏感度、表现、进展和治疗反应。现代大数据分析显示，大多数 我们中的大多数人对大多数疾病的易感性“一般”，但我们每个人对少数疾病的风险都很高。这一发现提供了 机遇与挑战--新兴基因组风险评估与管理 (EMERGEgram)倡议-识别常见疾病的高危人群，以促进预防或及早 治疗。我们在此提出一个计划，该计划建立在十多年的增长和关键支持知识的基础上 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 自该网络建立以来，医学和经验作为富有成效的参与者不断涌现。具体而言 目标1，我们将开发和验证基因组风险评估工具，以识别常见疾病的高危人群 疾病。基因组风险评估将包括多基因风险评分、家族健康史和 临床疾病预测指标。我们建议eMERGEgram指导委员会选择符合以下条件的疾病 可遗传；显示跨祖先的可变影响；与可用的早期检测、预防或 治疗干预措施；其中大型多血统全基因组关联研究可用于 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、慢性肾脏疾病、2型糖尿病、子宫肌瘤和结直肠癌。在具体目标2中，我们 将建立在Emerge-3、我们所有人以及我们由NIH支持的招聘创新中心的经验基础上 执行一项计划，吸引、招募和留住2,500名受试者(占人数不足人口的35% 在生物医学研究中)，包括家庭二人或三人组。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情况，并将这些交付给 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和影响的吸收和影响 基因组风险评估的组成部分在多大程度上提供独立的信息 种群和亚群内。我们将在我们的&>100,000条记录中使用共享的DNA片段映射 Biobank将开发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 没有大血统，就像小家庭或领养家庭的情况一样。其他研究目标将是 由参与者推动，在1-2年内通过焦点小组的社区参与发展，并高度 在整个项目中有意识地与参与者互动。

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.