权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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：
10207727
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/10207727
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 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 Subgroup Testing Underrepresented Populations United States National Institutes of Health Uterine Fibroids Validation Variant Vision 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.

精准医疗的概念建立在一个古老的认识之上，即人类的疾病各不相同