A Personalized Genomic Medicine Pilot Program Using the NJgene eMERGE Experience

描述(申请人提供)：人类基因组计划的一个承诺是使基因组信息个性化医学成为可能。在过去的四年里，西北大学一直是Emerge网络中的一个网站。这个连接到电子健康记录(EHR)的生物库联盟开发了便携算法，从EHR数据中识别病例和对照，然后执行全基因组关联研究(Gwas)，以在广泛测量的实验室值中将遗传变异与疾病和正常生理变异相关联。作为对RFA-HG-10-009的响应，我们建议为额外表型算法的网络开发和西北Emerge队列的基因数据分析做出贡献，并补充大约3,000个额外的EHR连锁样本，每个样本与660k GWAS型相关。我们将开发一系列的表型，使我们能够评估患者和医生对遗传信息在预测疾病易感性、药物反应和治疗结果中的作用的态度。在这些咨询的基础上，我们建议开发一种改进的质量改进模型，用于在先导性研究中确定哪些基因可能是临床护理环境中最有价值的。我们将开发一个同意模型和相关的教育方法，以支持在临床接触中向实验受试者提供基因信息，包括为研究目的而对先前进行基因分型的参与者进行CLIA认证的重新基因分型。在西北大学，我们利用广泛部署的商业EHR，EPIC，并建议开发技术方法，将基因变异数据集成到健康记录中，并使用护理点决策支持工具有效地将这些结果呈现给医生。这项工作的一个目标是在网络内协作开发最佳做法，以报告遗传变异数据，并制定在初级保健临床中使用遗传数据的当地实践指南。最后，我们建议对这些方法对初级保健医生及其患者的影响进行严格评估，确定监管问题，然后传播经验教训和最佳实践建议。总之，拟议的工作应该提供对基因组信息个性化医学的关键要素的评估。 相关性：这个项目开始回答有关使用基因组分析并将其应用于现实世界临床情况的问题。我们建议在不同的初级保健患者和医生群体中研究基因组变异的临床和个人效用。

DESCRIPTION (provided by applicant): One promise of the human genome project was to enable genome-informed personalized medicine. During the past four years Northwestern has been a site in the eMERGE network. This consortium of biobanks linked to electronic health records (EHR) has developed portable algorithms to identify cases and controls from EHR data and then performed genome-wide association studies (GWAS) to correlate genetic variation with disease and normal physiological variation in widely measured laboratory values. In response to RFA-HG-10-009, we propose to contribute to the network development of additional phenotype algorithms and the analysis of the genotype data from the Northwestern eMERGE cohort supplemented by approximately 3,000 additional EHR-linked samples, each associated with 660k GWAS genotypes. We will develop a range of phenotypes that will allow us to assess patient and physician attitudes to the utility of genetic information in predicting disease susceptibility, drug response and therapeutic outcomes. Based on these consultations, we propose to develop a modified quality improvement model for determining, in a pilot study, which genotypes might be most valuable to present in a clinical care setting. We will develop a consent model and associated educational methods in support of providing experimental subjects with genotype information in a clinical encounter, including CLIA certified re-genotyping of participants who were previously genotyped for research purposes. At Northwestern, we utilize a widely-deployed, commercial EHR, EPIC, and propose to develop technical approaches for integrating genetic variation data into the health record and to effectively present these results using point-of-care, decision support tools to physicians. A goal of this effort is to develop best practices collaboratively within the network, for reporting of genetic variation data and developing local practice guidelines for using genetic data in primary care clinical encounters. Finally, we propose a rigorous assessment of the impact of these approaches on primary care physicians and their patients, defining the regulatory issues and then disseminating lessons learned and best practice recommendations. Together, the work proposed should provide an assessment of key elements of genome-informed personalized medicine. RELEVANCE: This project begins to answer questions about using genomic analysis and applying it to real world clinical situations. We propose to study the clinical and personal utility of genomic variation in a diverse primary care patient and physician population.