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: 10611345
• 负责人: Wendy K Chung
• 金额: $ 150.13万
• 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/10611345
• 关键词: Acceleration; 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; Educational Models; Electronic Health Record; Electronic Medical Records and Genomics Network; Electronics; Engineering; Ensure; Ethnic Population; European; European ancestry; Extensible Markup Language; Family; Focus Groups; Funding; Genetic; Genetic Risk; Genetic Structures; Genomic medicine; Genomics; Goals; Health; Health Status; Height; Hospitals; Individual; Informatics; Institutional Review Boards; Kidney; Knowledge; Learning; Link; Measures; Medical Genetics; Medical center; Methods; National Center for Advancing Translational Sciences; Natural Language Processing; New York City; Participant; Patient Preferences; Patient Recruitments; Patients; Performance; Phenotype; Plug-in; 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; Risk Reduction; Stratification; Structure; Systems Biology; Technology; Testing; Text; Universities; Variant; Washington; clinical research site; clinical risk; community engagement; cost effectiveness; data modeling; data sharing; design; discrete data; diverse data; ethical, legal, and social implication; ethnic diversity; experience; genetic risk assessment; genetic testing; genetic variant; genome wide association study; genome-wide; genomic data; genomic predictors; health disparity; high risk; improved; individual patient; interoperability; literacy; malignant breast neoplasm; mathematical ability; medical specialties; medically underserved; member; patient oriented; phenotyping algorithm; polygenic risk score; portability; precision medicine; programs; prospective; public health relevance; racial diversity; racial population; rare variant; recruit; risk perception; risk prediction; screening; socioeconomics; 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.

项目概要/摘要 最近，大规模全基因组关联研究（GWAS）为大量多基因相关性提供了证据。 然而，这些研究大多数是在2017年进行的。 欧洲人需要新的数据和方法来针对非欧洲人定制多基因风险预测，以 确保基因组分层不会进一步加剧健康差异。 eMERGE-IV 网络将利用不同人群的遗传和电子健康记录 (EHR) 数据来 设计、验证和测试针对常见疾病的血统定制多基因风险评分的临床效用。 哥伦比亚大学是 eMERGE 网络的当前成员，已显着推进其目标， 招募了超过 2,500 名不同的患者进行测序并返回可操作的结果，从而努力 将网络过渡到 OMOP 通用数据模型，以提高效率、准确性、再现性和 电子表型的可移植性，并为构建基因测试提供广泛采用的 XML 解析器 自从我们上次申请以来，哥伦比亚精准医学计划也不断发展，现在包括在内。 参与多项国家举措，例如“全民计划”，我们在该计划中展示了我们的 能够快速招募生物医学研究中代表性不足的患者。 凭借我们以患者为中心的研究和社区参与社会经济的悠久传统， 曼哈顿北部的种族和民族多元化社区使我们能够成功地为 eEMERGE-IV 网络的增强多样性临床站点我们将利用我们之前的经验。 eMERGE、科学专业知识以及通过参与其他国家精准医学获得的知识 开发、优化、验证和传播针对血统的基因组风险评估和临床的举措 在目标 1 中，我们将通过贡献可共享的自然物质继续推进电子表型分析。 用于将临床文本转换为基于 OMOP 的离散数据并促进表型的语言处理工具 在目标 2 中，我们将开发和优化精确的祖先定制的全基因组多基因。 预测因子，将其与临床风险预测相结合，并测试其在不同人群中的表现。 3，我们将通过确定来调查与向不同患者返回健康风险预测相关的 ELSI 问题 通过焦点小组听取患者、新移民和 IRB 成员的意见 在目标 4 中，我们将开发便携式 EHR。 使用集成基因组数据、家族数据促进前瞻性风险沟通和管理的插件 在目标 5 中，我们将招募 2,500 名不同的患者并使用随机对照试验。 设计评估基因组预测的回归对风险感知、健康的准确性的影响 该提案将解决遗传风险方面的主要知识差距。 对不同人群进行评估，所获得的解决方案和知识将广泛适用于 针对许多临床专业的常见复杂特征的精准医学。

项目成果

Big Data Reveal Insights into Alopecia Areata Comorbidities.

• DOI: 10.1016/j.jisp.2017.10.006
• 发表时间: 2018-01-01
• 期刊: The journal of investigative dermatology. Symposium proceedings
• 作者: Lim, Chean Ping;Severin, Rachel K;Petukhova, Lynn
• 通讯作者: Petukhova, Lynn

Studying the impact of translational genomic research: Lessons from eMERGE.

• DOI: 10.1016/j.ajhg.2023.05.011
• 发表时间: 2023-07-06
• 期刊: American journal of human genetics
• 影响因子: 9.8

Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization.

使用孟德尔随机化研究肥胖遗传风险与术后并发症的关联。

• DOI: 10.1007/s00268-019-05202-9
• 发表时间: 2020
• 期刊: World journal of surgery
• 影响因子: 2.6
• 作者: Robinson,JamieR;Carroll,RobertJ;Bastarache,Lisa;Chen,Qingxia;Mou,Zongyang;Wei,Wei-Qi;Connolly,JohnJ;Mentch,Frank;Sleiman,Patrick;Crane,PaulK;Hebbring,ScottJ;Stanaway,IanB;Crosslin,DavidR;Gordon,AdamS;Rosenthal,Elisabet
• 通讯作者: Rosenthal,Elisabet

Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions.

• DOI: 10.1186/s12911-022-01759-z
• 发表时间: 2022-01-28
• 期刊: BMC medical informatics and decision making
• 影响因子: 3.5
• 作者: Yu J;Pacheco JA;Ghosh AS;Luo Y;Weng C;Shang N;Benoit B;Carrell DS;Carroll RJ;Dikilitas O;Freimuth RR;Gainer VS;Hakonarson H;Hripcsak G;Kullo IJ;Mentch F;Murphy SN;Peissig PL;Ramirez AH;Walton N;Wei WQ;Rasmussen LV
• 通讯作者: Rasmussen LV

Impact of cervical effacement and fetal station on progress during the first stage of labor: a biexponential model.

宫颈消失和胎儿位置对第一产程进展的影响：双指数模型。

• DOI: 10.1055/s-0033-1359721
• 发表时间: 2014
• 期刊: American journal of perinatology
• 影响因子: 2
• 作者: Quincy,MariaME;Weng,Chunhua;Shafer,StevenL;Smiley,RichardM;Flood,PamelaD;Mirza,FadiG
• 通讯作者: Mirza,FadiG