Genomic Basis of Susceptibility to COVID-19 Infection and its Complications

COVID-19 感染及其并发症易感性的基因组基础

• 批准号: 10165210
• 负责人: Iftikhar J Kullo
• 金额: $ 28.28万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-15 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10165210
• 关键词: 2019-nCoV; ABO blood group system; Affect; Age; American Heart Association; Arrhythmia; Biology; Blood Coagulation Disorders; COVID-19; COVID-19 pandemic; Cardiovascular system; Cessation of life; Computerized Medical Record; Cytokine Receptors; DNA; Data; Disease; Economics; Electronic Health Record; Electronic Medical Records and Genomics Network; Genes; Genetic; Genomic approach; Genomics; Goals; HLA Antigens; Health system; Individual; Infarction; Infection; Inflammasome; Informatics; Life; Link; Medical; Molecular; Morbidity - disease rate; Natural Immunity; Participant; Pathway interactions; Patients; Pattern; Phenotype; Play; Positioning Attribute; Predisposing Factor; Predisposition; Registries; Research; Research Personnel; Risk stratification; Sampling; Severities; Severity of illness; Signal Pathway; Site; Susceptibility Gene; Testing; Thrombosis; Translating; United States National Institutes of Health; Variant; Virus Diseases; Work; adaptive immunity; adverse outcome; biobank; case control; comorbidity; coronavirus disease; cytokine; cytokine release syndrome; drug development; experience; genetic variant; genome wide association study; genomic data; implementation science; improved; improved outcome; interest; mortality; myocardial injury; novel; pandemic disease; pathogen; patient registry; phenotyping algorithm; polygenic risk score; rare variant; response

PROJECT SUMMARY In addition to causing millions of cases and hundreds of thousands of deaths, the Coronavirus disease 2019 (COVID-19) pandemic has brought life and economic activity to a near standstill in many parts of the world. A coordinated scientific effort is necessary to mitigate the widespread misery, morbidity and mortality inflicted by the pandemic. The goal of this supplemental application is to contribute to informatics and genomics efforts to identify the genomic basis of susceptibility to and complications of COVID-19. The wide spectrum of disease severity with COVID-19 is only partially explained by age and medical comorbidities and genetic factors are likely to play a key role. Identifying genomic factors impacting COVID-19 case status and complications is important for risk stratification, identifying new pathophysiologic pathways for drug development/repurposing, and improved understanding of the biology of SARS-CoV-2 infection and its complications. As part of the electronic Medical Records and Genomics (eMERGE) since its inception in 2007, Mayo investigators have considerable experience in using the electronic health record (EHR) for genomics research. We will develop electronic phenotyping algorithms to ascertain COVID-19 case status, complications and fatality, to identify genomic variants associated with adverse outcomes. Using DNA samples linked to the EHR, we will perform genomic analyses to identify common and rare variants associated with case status, case severity and case mortality. We will collaborate with health systems and consortia in the US and around the world to increase the power and rapidity of the genomic studies. Our specific aims are: Specific Aim 1: Develop and validate electronic phenotyping algorithms to ascertain COVID-19 related phenotypes including case control status, i.e., individuals tested and those were identified to be positive for COVID-19, and disease severity, in particular cardiovascular complications including myocardial injury/infarction, arrhythmias, coagulopathy as well as large vessel thrombosis. Specific Aim 2: Perform genomic association analyses to identify variants associated with susceptibility to infection with SARS-CoV-2 and its complications. We will compare test +ve vs test -ve individuals, mild vs hospitalized cases of COVID-19 and among the latter those who develop severe disease or die. In addition to genome-wide association studies (GWAS), we will conduct association studies of the HLA region and burden tests using sequence data.

项目摘要 除了造成数百万例和数十万人死亡之外，冠状病毒还 2019年疾病（Covid-19）大流行使生活和经济活动几乎停滞不前 世界许多地方。必须进行协调的科学努力，以减轻广泛 大流行造成的痛苦，发病率和死亡率。这种补充的目标 应用是为信息学和基因组学的贡献做出贡献，以确定基因组基础 COVID-19的敏感性和并发症。广泛的疾病严重程度 Covid-19仅由年龄和医学合并症和遗传因素部分解释 可能扮演关键角色。识别影响COVID-19病例状态和的基因组因素和 并发症对于风险分层很重要，确定了新的病理生理途径 药物开发/重新利用，并提高对SARS-COV-2生物学的了解 感染及其并发症。 自2007年成立以来，作为电子病历和基因组学（出现）的一部分， 梅奥调查人员在使用电子健康记录（EHR）方面具有丰富的经验 基因组学研究。我们将开发电子表型算法以确定COVID-19 病例状态，并发症和死亡，以识别与不良相关的基因组变异 结果。使用与EHR链接的DNA样品，我们将执行基因组分析以识别 常见和稀有变体与案件状态，病例严重性和病例死亡率相关。我们 将与美国和世界各地的卫生系统和财团合作以增加 基因组研究的能力和速度。我们的具体目的是：特定目标1：开发 并验证电子表型算法以确定COVID-19相关表型 包括案件控制状态，即经过测试的个体，而被确定为阳性 COVID-19和疾病的严重程度，特别是心血管并发症，包括心肌并发症 损伤/梗塞，心律不齐，凝结病以及大血栓形成。具体目标2： 进行基因组关联分析，以识别与易感性相关的变体 SARS-COV-2及其并发症感染。我们将比较测试 +VE VS测试-VE 个人，轻度与住院的案例，即19日，后者 严重的疾病或死亡。除了全基因组关联研究（GWAS）外，我们还将进行 使用序列数据对HLA区域和负担测试的关联研究。