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| VGER: the Vanderbilt Genome Electronic Records project | |
|---|---|
| Investigator (PI): | Roden, Dan M; Denny, Joshua Charles |
| Performing Organization (PO): |
(Current): Vanderbilt University Medical Center, Department of Medicine, Division of Clinical Pharmacology / (615) 322-3384 |
| Supporting Agency (SA): | National Institutes of Health (NIH), National Human Genome Research Institute (NHGRI) |
| Initial Year: | 2015 |
| Final Year: | 2020 |
| Record Source/Award ID: | RePorter/U01HG008672 |
| Funding: | 2015 Award Amount: $838,369 2016 Award Amount: $923,697 2017 Award Amount: $820,603 2018 Award Amount: $1,837,013 2019 Award Amount: $704,230 |
| Award Type: | Grant |
| Award Information: | Reports resulting from this project |
| Abstract: | With their introduction into practice over the last two decades, electronic medical records (EMRs) have become increasingly recognized as platforms to not only improve delivery of care to the individual but also to understand variability in domain such as disease presentation and outcomes or quality assurance. Coupling dense genomic information to EMRs in eMERGE has provided tools for both discovery and initial implementation in genomic medicine, while raising new challenges and opportunities for using genomic data in health care. These include developing and mining the large datasets necessary to identify groups of patients with extreme phenotypes or rare genotypes, identifying clinically relevant subsets of common diseases, and identifying actionable genomic variants and determining how best to deploy these in a learning health care system. Building on our experience and contributions to eMERGE I and eMERGE II, we propose here three specific aims to address these challenges. In specific aim 1, we will expand the network's phenotyping library by creating increasingly granular phenotype definitions that identify specific subsets of disease with predictable clinical courses or response to therapies. Genotype phenotype relations will be studied by GWAS and advanced PheWAS methodology we have developed. In specific aim 2, we will identify rare variants with strong associations with human traits by resequencing 100 genes in 2,500 subjects at our center as part of the eMERGE III 25,000 patient cohort. We propose studying genes with variants known to affect human health and drug responses, and variants that our preliminary PheWAS analysis implicates as robust markers of important human phenotypes. In specific aim 3, we will expand PREDICT, our pre-emptive pharmacogenomic implementation program, to develop a pipeline that will deliver actionable variants to patients and providers and to assess their response. We will collaborate across eMERGE to develop, implement, and assess tools to deliver new information, measuring impact to ensure optimal benefit to patients. By executing these discovery and implementation aims, our site and the eMERGE network will contribute importantly to advancing the vision of genomic medicine as a contributor to modern health care. |
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| Country: | United States |
| State: | Tennessee |
| Zip Code: | 37232 |
| UI: | 20181415 |
| Project Status: | Completed |
| Related Records: | Vanderbilt Genome-Electronic Records project |
| Record History: | ('2019: Project extended to 2020',) |