Development and Use of Network Infrastructure for High-Throughput GWA Studies

高通量 GWA 研究网络基础设施的开发和使用

• 批准号: 7921317
• 负责人: Eric B Larson
• 金额: $ 11.85万
• 依托单位: KAISER FOUNDATION HEALTH PLAN OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-27 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7921317
• 关键词: Abbreviations; Accounting; Address; Adult; Adverse event; Age; Alzheimer' s Disease; Alzheimer' s Disease patient registry; Blood Pressure; Cancer Research Network; Carotid Arteries; Carotid Artery Diseases; Cholesterol; Chronic Disease; Clinic; Clinical; Clinical Data; Cognition; Collaborations; Communities; Complement; Computerized Medical Record; Consensus; Consent; Creatinine; Data; Data Collection; Data Set; Data Sources; Databases; Dementia; Development; Diagnosis; Disease; Disease Progression; Electronics; Enrollment; Environmental Exposure; Exposure to; Focus Groups; Foundations; Fred Hutchinson Cancer Research Center; Funding; Genomics; Genotype; Gold; Health; Healthcare; Healthcare Systems; High Density Lipoproteins; Individual; Inpatients; Knowledge; Laboratories; Leadership; Life; Link; Malignant Neoplasms; Maps; Medical; Meta-Analysis; Methods; Myalgia; National Cancer Institute; National Human Genome Research Institute; National Institute on Aging; Natural Language Processing; Neurofibrillary Tangles; Outcome; Outpatients; Participant; Pathology; Patients; Performance; Persons; Pharmaceutical Preparations; Pharmacogenetics; Pharmacy facility; Phenotype; Population; Prevention; Procedures; Process; Public Domains; Public Health; Quality of Care; Radiology Specialty; Recommendation; Recruitment Activity; Research; Research Ethics Committees; Research Infrastructure; Research Personnel; Resources; Risk Factors; Sampling; Senile Plaques; Series; Single Nucleotide Polymorphism; Site; Statistical Methods; System; Testing; Text; Time; Universities; Ursidae Family; Washington; Work; abstracting; base; biobank; case control; cohort; cost; data sharing; development policy; economic cost; gene environment interaction; genome wide association study; genome-wide; health care delivery; human disease; improved; interest; member; population based; prospective; success; trait; virtual

DESCRIPTION (provided by applicant): Linking biorepositories of patients in healthcare delivery systems with electronic medical records (EMRs) is an efficient strategy for high-throughput genome wide association (GWA) studies, as phenotype, covariable and exposure data of public health importance can be economically abstracted and pooled across delivery systems to facilitate the large numbers of subjects needed for GWA studies of each phenotype. Key obstacles to the success of this strategy remain. In this project, which will use population-based genomic and phenotype data from a well characterized population served by a delivery system which captures virtually all health care encounters in its data bases. Researchers from Group Health Cooperative's Center for Health Studies, the University of Washington, and the Fred Hutchinson Cancer Research Center will address these obstacles by pursuing the following specific aims: 1. Informed by results from targeted focus groups, implement a consensus process with key stakeholders to develop recommendations concerning consent, data sharing, and return of research results to subjects. 2. Work together with other network sites to develop a virtual data warehouse (VDW) analogous to that used in the Cancer Research Network, and extend natural language processing (NLP) to pathology, radiology, and clinical chart notes. 3. Develop and test strategies to determine whether each candidate EMR-based phenotype is sufficiently valid to pursue analyses of GWA data, and develop statistical methods that explicitly account for heterogeneous phenotype validity within and between sites. 4. Perform a series of GWA analyses in the GHC biorepository and linked biorepositories. 4a: Alzheimer's disease (AD). 4b: Carotid artery atherosclerotic disease (CAAD). 4c: Complications of statin use, including elevations of CPK and muscle pain. Through cooperation with other investigators and the NHGRI, this work will facilitate development of policies and procedures to realize the incredible potential of EMR-linked biorepositories for GWA studies to improve understanding, prevention and treatment of chronic diseases and illnesses. Specific GWA research will allow us to explore both etiologic research (AD and CAAD progression) and pharmacogenetics (statin therapy). The implications of this portfolio of research extend far beyond the specific phenotypes we have chosen to emphasize; we expect this work represents the beginning of a large and productive enterprise.

描述（由申请人提供）：将医疗保健输送系统中患者的生物疾病与电子病历（EMRS）联系起来，是高通量基因组广泛关联（GWA）研究的有效策略，作为表型，协变量和公共卫生重要性的暴露数据，可以经济上抽象地抽象和跨越主题的跨系统进行大量研究，以促进各种受试者的研究。这项策略成功的关键障碍仍然存在。在这个项目中，该项目将使用基于人群的基因组和表型数据，这些数据来自由递送系统提供的良好特征人群，该数据几乎可以捕获其数据基础中的所有医疗保健遇到。小组卫生合作社健康研究中心，华盛顿大学和弗雷德·哈钦森癌症研究中心的研究人员将通过追求以下具体目标来解决这些障碍： 1。在有针对性焦点小组的结果中得出的信息，与主要利益相关者实施共识过程，以开发有关同意，数据共享和研究结果回报对受试者的建议。 2。与其他网络站点一起开发类似于癌症研究网络中使用的虚拟数据仓库（VDW），并将自然语言处理（NLP）扩展到病理学，放射学和临床图表注释。 3。制定和测试策略，以确定每个基于EMR的表型是否足以进行GWA数据的分析，并开发统计方法，以明确说明站点内和站点之间的异质表型有效性。 4。在GHC生物座位上执行一系列GWA分析，并连接了生物固定剂。 4A：阿尔茨海默氏病（AD）。 4B：颈动脉动脉粥样硬化疾病（CAAD）。 4C：他汀类药物的并发症，包括CPK和肌肉疼痛的升高。 通过与其他研究人员和NHGRI的合作，这项工作将有助于制定政策和程序，以实现与GWA研究的EMR链接生物局体的难以置信的潜力，以提高对慢性疾病和疾病的理解，预防和治疗。特定的GWA研究将使我们能够探索病因研究（AD和CAAD进展）和药物遗传学（他汀类药物治疗）。这项研究组合的含义远远超出了我们选择强调的特定表型。我们希望这项工作代表了大型企业的开始。