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HeartShare DeCODE-HF: Data translation center to Combine Omics, Deep phenotyping, and Electronic health records for Heart Failure subtypes and treatment targets

HeartShare DeCODE-HF: Data translation center to Combine Omics, Deep phenotyping, and Electronic health records for Heart Failure subtypes and treatment targets
HeartShare DeCODE-HF:数据翻译中心,结合组学、深度表型分析和电子健康记录,了解心力衰竭亚型和治疗目标
批准号:
10488276
负责人:
ABEL N KHO
金额:
$334.01万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-09-13 至 2026-06-30

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中文摘要
翻译
项目摘要 西北HeartShare DeCODE-HF的总体目标:数据转换中心到联合收割机 心力衰竭亚型和治疗的组学、深度表型和电子健康记录 目标是为HeartShare提供全面管理和监督,包括协调和 在项目的所有子部分和核心以及与4个HeartShare临床中心之间进行沟通 (CC)。数据翻译中心(DTC)需要确保及时完成回顾, HeartShare的潜在组成部分。在我们的申请中,我们证明了以下人员的能力和先前的经验: 我们的多PI团队和核心领导者在大规模,多中心研究的开展和领导,特别是 在射血分数保留的心力衰竭(HFpEF)领域,基于电子健康记录(EHR)的 调查,深度表型分析,机器学习和生物储存库。对于回顾性和 未来的HeartShare组件,西北DTC将利用其在以下方面的丰富经验:(1) 队列和试验,有关于裁定的HF患者的数据,和(2)其领导和跟踪记录,作为最高的 参加HFpEF试验/研究,以确保HeartShare CC的最佳招募。我们还将利用我们的 HFpEF,数据协调/管理,BioData Catalyst,基于EHR的研究,生物统计学, 机器学习、多组学、人机交互和移动的健康数据监测,以(1) 成功执行HeartShare计划,(2)满足HeartShare DTC提供丰富的 为研究界提供资源,以推进下一代表型组学科学,以识别HFpEF 亚型和治疗靶点。我们的HeartShare DTC将履行其4项主要职责。(一) 行政和外联核心将监督HeartShare计划的运作,研究技能 开发,并按人头向CC支付深度表型成本;支持呼叫中心跟踪患者结局; 并促进临床和分子数据的快速和广泛的数据共享。(2)数据门户核心将作为 所有HeartShare数据的主要接入点(通过基于网络的界面)和协调中心;以及 开发面向患者的交互式网络界面,用于远程同意、填写表格和收集 的移动的健康数据。(3)数据管理核心将监督并确保数据 各种数据类型的质量、集成和协调;执行高级分析;协调 生物标本和成像生物储存库;并与TOPMed集成进行组学分析。(4)队列核心 将从已完成的流行病学队列和HF试验中汇总HF患者的数据,并将联合收割机数据 并对现有样品进行进一步的生物分析,以发现/验证新的靶点。
英文摘要
PROJECT SUMMARY The Overarching Aim of the Northwestern HeartShare DeCODE-HF: Data translation center to Combine Omics, Deep phenotyping, and Electronic health records for Heart Failure subtypes and treatment targets is to provide overall management and oversight for HeartShare, including coordination and communication across all subsections and cores of the program, and with the 4 HeartShare Clinical Centers (CCs). The Data Translation Center (DTC) will need to ensure timely completion of the retrospective and prospective components of HeartShare. In our application, we demonstrate the ability and prior experience of our multi-PI team and core leaders in the conduct and leadership of large-scale, multi-center studies, particularly in the realms of heart failure with preserved ejection fraction (HFpEF), electronic health record (EHR)-based investigation, deep phenotyping, machine learning, and biorepositories. For both the retrospective and prospective HeartShare components, the Northwestern DTC will leverage its considerable experience in: (1) cohorts and trials that have data on adjudicated HF patients, and (2) its leadership and track record as the top enroller in HFpEF trials/studies to ensure optimal recruitment by the HeartShare CCs. We will also leverage our expertise in HFpEF, data coordination/management, BioData Catalyst, EHR-based research, biostatistics, machine learning, multi-omics, human-computer interaction, and mobile health data monitoring to (1) successfully execute the HeartShare program and (2) meet the HeartShare DTC goals of providing a rich resource to the research community to advance the science of next-generation phenomics to identify HFpEF subtypes and therapeutic targets. Our HeartShare DTC will carry out each of its 4 primary responsibilities. (1) The Administrative and Outreach Core will oversee HeartShare program operations, research skills development, and capitation to CCs for deep phenotyping costs; support a call center to follow patient outcomes; and promote rapid and broad data-sharing of clinical and molecular data. (2) The Data Portal Core will serve as the primary access point (via a web-based interface) and coordinating center for all HeartShare data; and to develop an interactive patient-facing web-based interface for remote consent, completion of forms, and collection of mobile health data using BioData Catalyst tools. (3) The Data Management Core will oversee ensure data quality, integration and harmonization of various data types; perform advanced analytics; coordinate biospecimen and imaging biorepositories; and integrate with TOPMed for omics analyses. (4) The Cohort Core will aggregate data on HF patients from completed epidemiology cohorts and HF trials and will combine data with further bioprofiling of existing samples to allow discovery/validation of novel targets.
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