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

项目总结：加速新冠肺炎人类宿主基因和表型数据的访问和共享 来自双胞胎研究的早期证据表明，大约50%的新冠肺炎疾病负担是 是由宿主遗传学决定的。对新冠肺炎主办方因素的识别将直接影响到 制定公共卫生干预战略和确定药物目标。有各种各样的 利用现有的遗传和临床数据进行的现有队列纵向研究，例如UK Biobank，Allfus， 23andMe，Ancestry.com，他们正在与现有队列参与者接触，以获取有关新冠肺炎疾病的信息 负担。新冠肺炎宿主遗传学倡议(新冠肺炎)是一个国际财团，旨在 结合来自人类队列的数据，识别新冠肺炎的宿主遗传关联。欧洲人 基因组-现象组档案(EGA)和NHGRI分析、可视化和信息学实验室空间 Anvil/Terra平台是组成数据共享和分析平台的创始合作伙伴。特惠津贴是一项 GA4GH驱动程序项目，并可以快速获取这些数据，从而实现伦理基因组数据共享。这延伸了 国际数据共享基础设施和进程，使人们能够访问人类控制的访问数据 与应对新冠肺炎大流行相关。 目标1：向新冠肺炎-华大基因数据共享平台提交的主机 EGA之前已经收到了来自144多个美国提交者的提交，美国的用户代表 占去年流传输8.6PB数据的总用户社区的33%。新冠肺炎大流行在望 要通过计划中的新行业协作(例如Ancestry.com、 Regeneron制药公司)。有机会开发新的提交模板和流程 以便更快速地提交遗传和表型数据。 目标2：新冠肺炎主机元数据协调 记录和收集新冠肺炎疾病负担的临床患者数据是一项关键要求。 使用各种格式、编码方案、调查和本体论收集表型信息。 使用新冠肺炎-华大基因数据词典，我们将构建一个通用的最小元数据模型，该模型将映射 跨新冠肺炎研究进行基因关联研究。 目标3：快速集成数据接入并流入新冠肺炎华大基因分析平台 快速整合新的人类基因分型和表型鉴定将是确定可靠和良好的 支持遗传关联。NHGRI铁锤和Terra平台将成为 新冠肺炎-HGI。我们将使用GA4GH标准提供快速数据访问和美国COVID- 19个数据。这将导致EGA和Anvil之间更快速、更无缝的人力数据流，以提供 新冠肺炎主办协会研究的额外力量