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:
- 金额:$ 144.81万
- 依托单位:
- 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:
- 关键词:Academic Medical CentersAddressAssessment toolBioethicsBiological MarkersBiomedical ResearchCaringChronic Kidney FailureClinicalClinical MedicineColorectal CancerCommunitiesComputerized Medical RecordCoronary ArteriosclerosisCoupledDNADataData AnalyticsData SetDetectionDevelopmentDisciplineDiseaseDisease ProgressionDisease susceptibilityEarly DiagnosisEarly identificationEarly treatmentElectronic Health RecordElectronic Medical Records and Genomics NetworkFamilyFamily health statusFocus GroupsFoundationsFutureGenomeGenomic medicineGenomicsGoalsGrowthHealthHealth PersonnelHealthcareHeritabilityHumanIndividualInformaticsInformation SciencesInterventionKnowledgeLinkMapsMethodsModelingModernizationNon-Insulin-Dependent Diabetes MellitusOutcome StudyParticipantPathogenicityPatientsPersonsPharmaceutical PreparationsPharmacogenomicsPhenotypePhysiologicalPopulationPredispositionPreventionPrevention approachProviderRecording of previous eventsRecordsResearchResourcesRiskRisk AssessmentRisk ManagementSamplingScienceSiteSubgroupTestingUnderrepresented PopulationsUnited States National Institutes of HealthUterine FibroidsValidationVariantVisionanalytical methodbiobankcare outcomesclinical decision supportclinical phenotypecohortcommunity engagementdisorder riskexperiencegenetic pedigreegenetic variantgenome wide association studyhealth care service utilizationhigh riskhuman old age (65+)improvedinnovationlarge datasetsmeetingsnovelpatient engagementpersonalized approachpersonalized carephenomepolygenic risk scoreprecision medicineprogramsrecruitresponsetooltraittreatment responseuptake
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
项目成果
期刊论文数量(0)
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{{ truncateString('DAN M RODEN', 18)}}的其他基金
Vanderbilt Genome-Electronic Records (VGER) Project
范德比尔特基因组电子记录 (VGER) 项目
- 批准号:
10771648 - 财政年份:2023
- 资助金额:
$ 144.81万 - 项目类别:
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 - 财政年份:2020
- 资助金额:
$ 144.81万 - 项目类别:
Functional Genomics of Cardiac Sodium Channel Variants
心脏钠通道变异的功能基因组学
- 批准号:
10538620 - 财政年份:2020
- 资助金额:
$ 144.81万 - 项目类别:
Vanderbilt Genome-Electronic Records (VGER) Project
范德比尔特基因组电子记录 (VGER) 项目
- 批准号:
10450009 - 财政年份:2020
- 资助金额:
$ 144.81万 - 项目类别:
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