EHR-based Genomic Risk Assessment and Management for Diverse Populations

基于 EHR 的不同人群基因组风险评估和管理

• 批准号: 10207714
• 负责人: Wendy K Chung
• 金额: $ 179.25万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10207714
• 关键词: Address; Adopted; Adoption; All of Us Research Program; Behavior; Biomedical Research; Chronic Disease; Clinical; Clinical Data; Clinical Management; Clinical Research; Collaborations; Colon Carcinoma; Communication; Communities; Complex; Coronary Arteriosclerosis; Cost Analysis; Data; Development; Diagnostic; Disease; Education; Electronic Health Record; Electronic Medical Records and Genomics Network; Engineering; Ensure; Ethnic group; European; Extensible Markup Language; Family; Focus Groups; Funding; Genetic; Genetic Risk; Genetic Structures; Genomic medicine; Genomics; Goals; Health; Health Status; Hospitals; Individual; Informatics; Institutional Review Boards; Kidney; Knowledge; Link; Measures; Medical Genetics; Medical center; Methods; Natural Language Processing; New York City; Participant; Patient Preferences; Patient Recruitments; Patients; Performance; Phenotype; Population Heterogeneity; Positioning Attribute; Precision Medicine Initiative; Prevention strategy; Primary Prevention; Provider; Public Health; Randomized Controlled Trials; Recommendation; Recording of previous events; Reporting; Reproducibility; Research; Risk; Risk Assessment; Risk Estimate; Risk Factors; Risk Management; Stratification; Systems Biology; Technology; Testing; Text; Translational Research; Universities; Variant; Washington; base; clinical research site; clinical risk; community engagement; cost effectiveness; data modeling; design; discrete data; diverse data; ethical legal social implication; ethnic diversity; experience; genetic risk assessment; genetic testing; genetic variant; genome wide association study; genome-wide; genomic data; health disparity; high risk; improved; individual patient; interoperability; literacy; malignant breast neoplasm; mathematical ability; medical specialties; medically underserved; member; patient oriented; polygenic risk score; portability; precision medicine; programs; prospective; public health relevance; racial and ethnic; racial diversity; rare variant; recruit; risk perception; risk prediction; screening; socioeconomics; structural genomics; tailored health care; tool; trait; trial design; underserved community; user centered design; validation studies

PROJECT SUMMARY/ABSTRACT Recently, large-scale genome-wide association studies (GWAS) provide evidence for a substantial polygenic contribution to the risk of many common complex diseases. However, most of these studies were performed in Europeans, and new data and methods are necessary to tailor polygenic risk prediction to non-Europeans, to ensure that genomic stratification does not further exacerbate health disparities. The overarching goal of the eMERGE-IV network is to leverage genetic and electronic health record (EHR) data for diverse populations to design, validate and test the clinical utility of ancestry-tailored polygenic risk scores for common diseases. As a current member of the eMERGE network, Columbia University has significantly advanced its goals, having recruited over 2,500 diverse patients for sequencing and return of actionable findings, leading the effort to transition the network to the OMOP Common Data Model to improve the efficiency, accuracy, reproducibility and portability of electronic phenotypes, and contributing a widely-adopted XML parser for structuring genetic test reports. Since our last application, the Columbia Precision Medicine Initiative has also grown and now includes participation in several national initiatives, such as the All-of-Us program, in which we have demonstrated our ability to rapidly recruit patients under-represented in biomedical research. Our scientific expertise combined with our strong tradition of patient-centered research and community engagement in a socioeconomically, racially, and ethnically diverse community of Northern Manhattan, positions us to successfully contribute as the Enhanced Diversity Clinical Site of the eEMERGE-IV network. We will leverage our prior experience with eMERGE, scientific expertise, and knowledge gained from participation in other national precision medicine initiatives to develop, optimize, validate and disseminate ancestry-tailored genomic risk assessment and clinical management tools. In Aim 1, we will continue to advance electronic phenotyping by contributing sharable natural language processing tools for converting clinical text into OMOP-based discrete data and facilitating phenotype interoperability. In Aim 2, we will develop and optimize accurate ancestry-tailored genome-wide polygenic predictors, integrate them with clinical risk predictions, and test their performance in diverse populations. In Aim 3, we will investigate ELSI issues related to the return of health risk predictions to diverse patients by ascertaining patients’, clinicians’, and IRB members’ views through focus groups. In Aim 4, we will develop portable EHR plug-ins to facilitate prospective risk communication and management using integrated genomic data, family history, and clinical data. In Aim 5, we will recruit 2,500 diverse patients and use a randomized controlled trial design to assess the impact of return of genomic prediction on the accuracy of risk perception, health surveillance, and risk reducing measures. This proposal will address major knowledge gaps in genetic risk assessment for diverse populations, and the solutions and knowledge gained will be broadly applicable to precision medicine for common complex traits across many clinical specialties.

项目摘要/摘要 最近，大规模基因组关联研究（GWAS）为实质性多基因提供了证据 对许多常见复杂疾病的风险做出的贡献。但是，这些研究大多数是在 欧洲人，以及针对非欧洲人量身定制多基因风险预测的新数据和方法是必要的 确保基因组分层不会进一步加剧健康差异。总体目标 Emerge-IV网络是利用遗传和电子健康记录（EHR）数据的数据 设计，验证和测试普通疾病的祖先鉴定多基因风险评分的临床实用性。作为 哥伦比亚大学现任网络的现任成员已大大提高了其目标， 招募了2500多名潜水员患者进行测序和可行发现的回报，导致了努力 将网络转换为OMOP公共数据模型，以提高效率，准确性，可重复性和 电子表型的可移植性，并贡献了一个广泛的XML解析器来构建基因检测 报告。自上次申请以来，哥伦比亚精密医学计划也已经成长，现在包括 参加几项国家计划，例如All-US计划，我们已经证明了我们的计划 能够快速招募生物医学研究中代表性不足的患者。我们的科学专业知识结合了 凭借我们以患者为中心的研究和社区参与社会经济的牢固传统， 曼哈顿北部的种族和种族多样化的社区，使我们能够成功地做出贡献 Eemerge-IV网络的增强多样性临床部位。我们将利用我们先前的经验 从参与其他国家精确医学中获得的出现，科学专业知识和知识 开发，优化，验证和传播祖先规定的基因组风险评估和临床的倡议 管理工具。在AIM 1中，我们将通过贡献自然的自然来继续推进电子表型 语言处理工具，用于将临床文本转换为基于OMOP的离散数据并支持表型 互操作性。在AIM 2中，我们将开发并优化准确的祖先详细基因组多基因 预测因素将它们与临床风险预测相结合，并在潜水员种群中测试其表现。目标 3，我们将通过确定对潜水员患者的健康风险预测返回与健康风险预测有关的ELSI问题 患者，临床医生和IRB成员通过焦点小组的观点。在AIM 4中，我们将开发便携式EHR 插件使用集成基因组数据促进预期风险沟通和管理，家庭 历史和临床数据。在AIM 5中，我们将招募2500名不同的患者，并使用随机对照试验 设计以评估基因组预测回报对风险感知准确性的影响的影响 监视和降低措施的风险。该提案将解决遗传风险的主要知识差距 评估不同人群的评估，而获得的解决方案和知识将广泛适用于 许多临床专业的普通复杂性状的精密医学。