VGER, the Vanderbilt Genome-Electronic Records Project

描述（由申请人提供）：在过去的二十年中，电子医疗记录（emr）被越来越多地认为是一个平台，不仅可以改善对个人的护理，还可以了解疾病表现和结果或质量保证等领域的可变性。在eMERGE中将密集的基因组信息与emr相结合，为基因组医学的发现和初步实施提供了工具，同时也为在医疗保健中使用基因组数据提出了新的挑战和机遇。这些包括开发和挖掘必要的大型数据集，以识别具有极端表型或罕见基因型的患者群体；确定临床相关的常见疾病亚群；识别可操作的基因组变异，并确定如何在学习型医疗保健系统中最好地部署这些变异。基于我们在“新兴一”和“新兴二”中的经验和贡献，我们在此提出应对这些挑战的三个具体目标。在Specific Aim 1中，我们将通过创建越来越细粒度的表型定义来扩展网络的表型库，以确定具有可预测临床病程或对治疗反应的疾病的特定亚群。基因型-表型关系将通过GWAS和我们开发的先进的PheWAS方法进行研究。在Specific Aim 2中，我们将通过对我们中心的2500名受试者（作为eMERGE-III 25,000名患者队列的一部分）中的100个基因进行重测序，确定与人类特征密切相关的罕见变异。我们建议研究具有已知影响人类健康和药物反应的变异的基因，以及我们的初步PheWAS分析暗示作为重要人类表型的强大标记的变异。在Specific Aim 3中，我们将扩展我们先发制人的药物基因组实施计划PREDICT，以开发一个管道，将可操作的变体提供给患者和提供者，并评估他们的反应。我们将与eMERGE合作开发、实施和评估工具，以提供新信息，衡量影响，确保患者获得最佳利益。通过执行这些发现和实现目标，我们的网站和eMERGE网络将为推进基因组医学作为现代医疗保健的贡献者的愿景做出重要贡献。

DESCRIPTION (provided by applicant): 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 healthcare. 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 healthcare 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 healthcare.