A Personalized Genomic Medicine Pilot Program Using the NJgene eMERGE Experience

描述（由申请人提供）：人类基因组计划的一个承诺是实现基于基因组的个性化医疗。在过去的四年里，西北大学一直是eMERGE网络中的一个站点。这个与电子健康记录（EHR）相关的生物库联盟开发了便携式算法，从电子健康记录数据中识别病例和对照，然后进行全基因组关联研究（GWAS），将遗传变异与广泛测量的实验室值中的疾病和正常生理变异联系起来。为了响应RFA-HG-10-009，我们建议为网络开发提供额外的表型算法，并对来自西北大学eMERGE队列的基因型数据进行分析，补充了大约3000个额外的ehr相关样本，每个样本与660k GWAS基因型相关。我们将开发一系列表型，这将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效用的态度。基于这些咨询，我们建议在一项初步研究中开发一种改进的质量改进模型，以确定哪些基因型可能在临床护理环境中最有价值。我们将开发一个同意模型和相关的教育方法，以支持在临床遇到时向实验对象提供基因型信息，包括CLIA认证的先前为研究目的进行基因分型的参与者的重新基因分型。在西北大学，我们利用广泛部署的商业电子病历、EPIC，并建议开发技术方法，将遗传变异数据整合到健康记录中，并使用即时护理和决策支持工具有效地向医生展示这些结果。这项工作的目标是在网络内协作开发最佳实践，以报告遗传变异数据并制定在初级保健临床就诊中使用遗传数据的地方实践指南。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，提出的工作应该提供基因组信息个性化医疗关键要素的评估。

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.