Establishing the GWAS Catalog as a resource for large-scale association studies

建立 GWAS 目录作为大规模关联研究的资源

• 批准号: 10165278
• 负责人: Fiona Cunningham
• 金额: $ 16.88万
• 依托单位: EUROPEAN MOLECULAR BIOLOGY LABORATORY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10165278
• 关键词: Address; Age; Archives; Authorization documentation; COVID-19; COVID-19 pandemic; Catalogs; Cessation of life; Clinical; Clinical Data; Code; Cohort Studies; Collaborations; Collection; Communities; Coupled; Data; Data Analyses; Data Science; Data Set; Development; Disease; Drug Targeting; Ensure; Environment; Ethics; European; Fast Healthcare Interoperability Resources; Finland; Gender; Genetic; Genetic study; Genome; Genotype; Health; Healthcare; Hospitalization; Hospitals; Human; Individual; Industrialization; Infection; Informatics; Infrastructure; Integration Host Factors; International; Intervention; Investments; Length of Stay; Life Style; Longitudinal cohort study; Maps; Measures; Mediating; Metadata; Methods; Modeling; National Human Genome Research Institute; Ontology; Parkinson Disease; Participant; Patients; Pharmacologic Substance; Phenotype; Policies; Process; Research; Research Personnel; Resources; Risk Factors; Role; Scheme; Secure; Semantics; Severity of illness; Source; Spain; Standardization; Stream; Surveys; Sweden; Symptoms; System; Time; Twin Studies; Visualization; base; biobank; burden of illness; cohort; comorbidity; coronavirus disease; data access; data dictionary; data integration; data sharing; demographics; design; disease heterogeneity; distributed data; genetic association; genome wide association study; genomic data; human data; improved; novel; personalized medicine; phenome; phenotypic data; public health intervention; sharing platform

PROJECT SUMMARY: Accelerating access and sharing of COVID-19 human host genetic and phenotype data Early evidence from twin studies suggests that approximately 50% of COVID-19 disease burden is determined by host genetics. The identification of host factors for COVID-19 will directly influence the development of public health intervention strategies and the identification of drug targets. There are a variety of existing cohort longitudinal studies with existing genetic and clinical data, e.g. UK Biobank, AllofUs, 23andMe, Ancestry.com who are engaging existing cohort participants for information on COVID-19 disease burden. The COVID-19 Host Genetics Initiative (COVID-19-HGI) is an international consortium that aims to identify host genetic associations of COVID-19 by combining data from human cohorts. The European Genome-phenome Archive (EGA) and the NHGRI Analysis, Visualization, and Informatics Lab-space AnVIL/Terra platforms are founding partners that form the data sharing and analysis platform. The EGA is a GA4GH driver project and can rapidly acquire these data enabling ethical genomic data sharing. This extends the international data sharing infrastructure and processes enabling access to human controlled access data relevant to addressing the COVID-19 pandemic. Aim 1: Host submissions to the COVID-19-HGI data sharing platform The EGA has previously received submissions from over 144 US submitters and US based users represent 33% of the total user community which streams 8.6 PB of data last year. The COVID-19 pandemic is expected to significantly increase this number through planned new industrial collaboration (e.g. Ancestry.com, Regeneron Pharmaceuticals). There is an opportunity to develop new submission templates and processes to enable more rapid submission of genetic and phenotype data. Aim 2: COVID-19 host metadata harmonisation Recording and collection of clinical patient data of COVID-19 disease burden is a critical requirement. Phenotype information is collected using a variety of formats, coding schemes, surveys, and ontologies. Using the COVID-19-HGI data dictionary, we will construct a common minimal metadata model that will map across COVID-19 studies for genetic association studies. Aim 3: Rapid integrated data access and flow into COVID-19-HGI analysis platform Rapid integration of new human genotypes and phenotyping will be essential to determine reliable and well supported genetic associations. The NHGRI AnVIL and Terra platform will be the analysis platform for the COVID-19-HGI. We will use GA4GH standards to provide rapid data access and integration of US COVID- 19 data. This will result in more rapid and seamless human data flow between EGA and AnVIL to provide additional power to COVID-19 host association studies

项目摘要：加速Covid-19人类宿主遗传和表型数据的访问和共享 双胞胎研究的早期证据表明，大约50％的covid-19疾病负担是 由宿主遗传学确定。 COVID-19的宿主因素的识别将直接影响 制定公共卫生干预策略和识别药物目标。有多种多样 现有的与现有遗传和临床数据的纵向研究，例如英国生物银行，Allofus， 23AndMe，Ancestry.com，他们正在吸引现有队列参与者以获取有关Covid-19疾病的信息 负担。 COVID-19-HOST GENETICS INTIATIVE（COVID-19-HGI）是一个国际财团，旨在 通过组合人类同类的数据来识别Covid-19的宿主遗传关联。欧洲 基因组 - 表现档案（EGA）和NHGRI分析，可视化和信息学实验室空间 Anvil/Terra平台是构成数据共享和分析平台的创始合作伙伴。 EGA是 GA4GH驱动程序项目，可以快速获取这些数据，从而实现道德基因组数据共享。这延伸 国际数据共享基础架构和流程可访问人类受控访问数据 与解决Covid-19-19的大流行有关。 AIM 1：主机提交到COVID-19-HGI数据共享平台 EGA先前已经收到了144多个美国提交者和美国用户代表的意见书 去年流式传输8.6 pb的用户社区的33％。预计Covid-19大流行 通过计划的新工业合作大大提高了这个数字（例如，Ancestry.com， Regeneron Pharmaceuticals）。有机会开发新的提交模板和流程 为了使遗传和表型数据更快地提交。 AIM 2：Covid-199主机元数据协调 记录和收集COVID-19疾病负担的临床患者数据是一个至关重要的要求。 使用多种格式，编码方案，调查和本体论收集表型信息。 使用COVID-19-HGI数据词典，我们将构建一个通用的最小元数据模型，该模型将映射 在共同研究的整个研究研究中，用于遗传关联研究。 AIM 3：快速集成数据访问并流入COVID-19-HGI分析平台 新的人类基因型和表型的快速整合对于确定可靠且井井有条至关重要 支持的遗传关联。 NHGRI ANVIL和TERRA平台将成为 COVID-19-HGI。我们将使用GA4GH标准来提供我们covid-的快速数据访问和集成 19数据。这将导致EGA和Anvil之间的更快，无缝的人类数据流以提供 COVID-19-19