Bridging the Gap between Genomics and Clinical Outcomes in CHD

缩小先心病基因组学与临床结果之间的差距

• 批准号: 10027913
• 负责人: MARTIN TRISTANI-FIROUZI
• 金额: $ 41.94万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2025-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10027913
• 关键词: Artificial Intelligence; Bayesian Network; Bioinformatics; Childhood; Clinical; Clinical Data; Clinical Research; Clinical and Translational Science Awards; Code; Collaborations; Complex; Custom; Data; Data Set; Dependence; Diagnostic; Disease Outcome; Electronic Health Record; Fostering; Foundations; Gender; Genes; Genomics; Genotype; Goals; Heart; Infrastructure; Institution; Interdisciplinary Study; Internet; Knowledge; Methodology; Modeling; Multicenter Studies; National Heart, Lung, and Blood Institute; Network-based; Online Systems; Outcome; Outcomes Research; Pathway interactions; Patients; Pediatric Cardiac Genomics Consortium; Pediatric cardiology; Phenotype; Readability; Recording of previous events; Research; Research Personnel; Resources; Risk Factors; Scientist; Site; Societies; Standard Model; Testing; Therapeutic; Thoracic Surgical Procedures; Training; Translating; Utah; Vision; Visit; Work; base; clinical care; clinical database; comorbidity; congenital heart disorder; data infrastructure; data resource; design; gene function; genomic data; improved; innovation; member; next generation; novel; outcome prediction; patient oriented; predict clinical outcome; programs; relational database; repository; skills; surgery outcome; tool

PROJECT SUMMARY/ABSTRACT The NHLBI has invested extensively in the Pediatric Cardiac Genomics Consortium (PCGC), recognizing that translating genomic discoveries into optimized management and therapeutic strategies for congenital heart disease (CHD) can only be achieved in the context of multi-center, collaborative research. Currently, the PCGC is lacking two fundamental capabilities that hinder its ability to define the genomic basis for CHD outcomes: (1) a robust mechanism for extracting pertinent, machine-readable clinical data from Electronic Health Records (EHRs) across multiple institutions; and (2) a robust Artificial Intelligence (AI) platform that is capable of teasing apart the complex interplay between maternal factors, phenotypes, genotypes, gene functions and clinical outcomes. Here, we propose innovative solutions to these challenges, by assembling teams of content experts to leverage existing infrastructure to extract relevant outcomes directly from the EHR of participating PCGC Centers and by designing best-practice AI tools for outcomes research. Our principal goal is provide the vision, infrastructure and expertise to collaboratively empower CHD outcomes research, foster knowledge exchange, and train the next generation of genomic scientists. We propose to leverage existing data infrastructure to obtain Electronic Health Records (EHR) and other clinical variables at scale by partnering with other research networks to create a PCGC Data Resource. Using this resource, we will create and deploy a platform of Artificial Intelligence (AI)-based predictors for CHD outcomes research, with the goal of translating genomic discoveries into improved management and therapeutic strategies for CHD.

项目概要/摘要 NHLBI 对儿科心脏基因组学联盟 (PCGC) 进行了大量投资，认识到 将基因组发现转化为先天性心脏病的优化管理和治疗策略 疾病（CHD）只能在多中心、协作研究的背景下才能实现。目前，PCGC 缺乏两项基本能力，阻碍其定义冠心病结果的基因组基础的能力：(1) 从电子健康记录中提取相关的、机器可读的临床数据的强大机制 （电子病历）跨多个机构； (2) 一个强大的人工智能 (AI) 平台，能够戏弄 除了母体因素、表型、基因型、基因功能和临床之间复杂的相互作用之外 结果。在这里，我们通过组建内容专家团队，提出针对这些挑战的创新解决方案 利用现有基础设施直接从参与 PCGC 的 EHR 中提取相关结果 中心并设计用于结果研究的最佳实践人工智能工具。我们的主要目标是提供愿景， 基础设施和专业知识，以协作增强先心病结果研究、促进知识交流、 并培训下一代基因组科学家。我们建议利用现有的数据基础设施来获取 通过与其他研究网络合作，大规模地提供电子健康记录 (EHR) 和其他临床变量 创建 PCGC 数据资源。使用此资源，我们将创建并部署一个人工平台 基于智能 (AI) 的 CHD 结果研究预测器，目标是转化基因组发现 改善冠心病的管理和治疗策略。