COVID-19: Multi-Omics Approach to Identify Molecular Mechanisms Responsible for Risk and Resilience to Adverse Outcomes

COVID-19：多组学方法来识别导致风险和不良结果恢复能力的分子机制

• 批准号: 10154323
• 负责人: CHARLES D SEARLES
• 金额: --
• 依托单位: VETERANS HEALTH ADMINISTRATION
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10154323
• 关键词: 2019-nCoV; Address; African American; Age; Angiotensin II; Arrhythmia; Attenuated; Biochemical Pathway; Biological; Biological Markers; Blood; Blood Banks; Blood specimen; Brain natriuretic peptide; C-reactive protein; COVID-19; COVID-19 mortality; COVID-19 pandemic; COVID-19 patient; COVID-19 test; COVID-19 testing; Cardiovascular Diseases; Cardiovascular system; Centers for Disease Control and Prevention (U.S.); Cessation of life; Characteristics; China; Clinical; Clinical Data; Congestive Heart Failure; Coronary Arteriosclerosis; Data; Databases; Development; Diabetes Mellitus; Disease; Disease Outcome; Disease Progression; Electronic Health Record; Enrollment; Epidemic; Epigenetic Process; Ethnic Origin; Europe; Fibrin fragment D; Fibrin split products; Health; High Prevalence; Hypertension; Immune; Immune response; Immunologic Markers; Infarction; Infection; Inflammation; Infrastructure; Interleukin-6; International; Intervention; Laboratories; Lead; Left; Logistic Regressions; Measurement; Measures; Mechanical ventilation; Medical center; Metabolic; Metabolic Pathway; Methods; MicroRNAs; Modeling; Molecular; Molecular Profiling; Myocardial; Myocarditis; Obesity; Outcome; Oxidative Stress; Participant; Pathologic; Pathway interactions; Patients; Pilot Projects; Plasma; Play; Positioning Attribute; Predisposition; Proteomics; Protocols documentation; Race; Renin; Renin-Angiotensin-Aldosterone System; Research; Residual state; Risk; Risk Factors; Role; SARS-CoV-2 infection; Sampling; Severity of illness; Stretching; Structure of respiratory epithelium; Testing; Therapeutic; Therapeutic Intervention; Troponin I; University Hospitals; Urokinase Plasminogen Activator Receptor; Veterans; Virus Diseases; Work; acute infection; adverse outcome; aminothiol; angiotensin I (1-7); biobank; cardiometabolic risk; cardiometabolism; cardiovascular health; cardiovascular risk factor; cell injury; clinical predictors; clinically relevant; cohort; differential expression; experience; extracellular; feature selection; heart circulation; hemodynamics; high risk; immune activation; indicated prevention; inflammatory marker; lung injury; member; men; metabolome; metabolomics; military veteran; molecular marker; mortality risk; multiple omics; myocardial injury; new therapeutic target; next generation sequencing; novel; novel marker; pandemic disease; patient registry; personalized intervention; precision medicine; predictive marker; predictive modeling; primary endpoint; prognostic; programs; prospective; repository; resilience; screening; secondary endpoint; severe COVID-19; sex; specific biomarkers; systemic inflammatory response; targeted treatment; therapeutic target; thrombogenesis

Objective: Emerging data from the COVID-19 pandemic indicate that men and African Americans have higher mortality, and cardiometabolic risk factors, including obesity, diabetes, and hypertension, cluster in patients who develop adverse outcomes to SARS-CoV-2 infection. The Veteran population is particularly vulnerable to COVID-19 because of the very high prevalence of cardiometabolic risk factors. However, not all Veterans with COVID-19 experience severe disease, and there is an urgent need to identify novel molecular pathways underlying risk and resilience to COVID-19. Previous work and preliminary studies from our team have demonstrated that targeted proteomics, metabolomics, and miRNA-omics can identify novel biomarkers and molecular pathways associated with cardiovascular health and disease. In this project, we will use a multi-omics to elucidate novel biomarkers and pathways associated with risk and resilience to severe COVID-19. Research Plan: In Aim 1, we will compare expression of pathway-specific biomarkers in hospitalized patients with severe COVID-19 with expression of these biomarkers in patients who do not develop severe COVID-19. Pathway-specific biomarkers reflecting activation of the renin-angiotensin-aldosterone system, systemic inflammation, oxidative stress, immune activation, thrombogenesis, and myocardial injury and stretch will be assessed. The primary endpoints for severe disease will be pathologic elevation of IL-6 levels or troponin I levels. Secondary endpoints will be requirement for mechanical ventilation, congestive heart failure, change in SOFA score, and death. In Aim 2, we will assess the extracellular miRNA and metabolomic profiles of the same two groups of hospitalized COVID-19 patients and determine miRNAs and metabolites differentially expressed between the two groups. Subsequently, we will examine connectivity between miRNA-metabolome networks and clinical endpoints in COVID-19 patients by performing an integrative analysis of differentially expressed miRNAs and metabolites, which will identify metabolic pathways associated with severe infection. Methods: The proposed studies will analyze de-identified blood samples and clinical data from COVID-19 patients hospitalized at the Atlanta VAMC and Emory University Hospital. The samples will be obtained from a bio repository that is currently banking residual plasma and serum from routine laboratory testing of COVID-19 patients. In Aim 1, we will measure levels of aminothiol (oxidative stress), suPAR (thrombogenesis/immune dysregulation), hsCRP (inflammation), hsTnI (myocardial injury), BNP (myocardial stretch), D-dimers (thrombogenesis), angiotensin II, angiotensin-(1-7) and plasma renin activity. Logistic regression modeling will be performed to identify biomarkers predictive of clinical endpoints. In Aim 2, we will use next generation sequencing, RT-qPCR, and high-throughput metabolomics profiling to assess expression of extracellular miRNAs and metabolites. A metabolome wide association study (MWAS) and ensemble feature selection (EFS) will be used to identify robust biomarkers and develop predictive models for severe COVID-19. Data from EFS analysis will input to the program xMWAS, which will determine connectivity between miRNA-metabolome networks and clinical outcomes. Clinical Relevance: Veterans with cardiovascular conditions are at higher risk for SARS-CoV-2 infection and severe disease progression. Our team has the infrastructure and methods in place to conduct in-depth, multi- omics studies to address predictors of adverse outcomes in Veterans with COVID-19 and identify epigenetic and cardiometabolic pathways that determine susceptibility to adverse outcomes. Furthermore, because 50% of the Veteran population at the Atlanta VA Medical Center Veteran is African American, we are in a unique position to address the role of race in susceptibility to severe COVID-19. Discovery of novel biomarkers and pathways associated with severe COVID-19 has broad implications for screening, therapeutics, and implementation of earlier personalized interventional strategies for attenuating adverse outcomes.

目的：COVID-19大流行的新数据表明，男性和非洲裔美国人的 死亡率和心脏代谢危险因素，包括肥胖、糖尿病和高血压，聚集在 对SARS-CoV-2感染产生不良后果。退伍军人特别容易受到 COVID-19，因为心脏代谢风险因素的患病率非常高。然而，并不是所有的退伍军人 COVID-19经历了严重的疾病，迫切需要确定新的分子途径 潜在风险和应对COVID-19的能力。我们团队以前的工作和初步研究 证明靶向蛋白质组学、代谢组学和miRNA组学可以鉴定新的生物标志物， 与心血管健康和疾病相关的分子途径。在这个项目中，我们将使用多组学 阐明与严重COVID-19风险和恢复力相关的新生物标志物和途径。 研究计划：在目标1中，我们将比较住院患者中通路特异性生物标志物的表达 在未发生严重COVID-19的患者中表达这些生物标志物。 反映系统性肾素-血管紧张素-醛固酮系统激活的途径特异性生物标志物 炎症、氧化应激、免疫激活、血栓形成和心肌损伤和牵张将是 评估。重度疾病的主要终点是IL-6水平或肌钙蛋白I水平的病理性升高。 次要终点为机械通气要求、充血性心力衰竭、SOFA变化 分数和死亡在目标2中，我们将评估这两种细胞的细胞外miRNA和代谢组学特征， 住院COVID-19患者组，并确定差异表达的miRNA和代谢物 两组之间的差异。随后，我们将研究miRNA-代谢组网络之间的连接， 和临床终点，通过对差异表达的 miRNAs和代谢物，这将确定与严重感染相关的代谢途径。 方法：拟议的研究将分析COVID-19的去识别血液样本和临床数据 在亚特兰大VAMC和埃默里大学医院住院的患者。样本将从一个 生物储存库，目前正在储存来自COVID-19常规实验室检测的残留血浆和血清 患者在目标1中，我们将测量氨基硫醇（氧化应激）、suPAR（血栓形成/免疫反应） 失调）、hsCRP（炎症）、hsTnI（心肌损伤）、BNP（心肌牵张）、D-二聚体 （血栓形成）、血管紧张素II、血管紧张素-（1-7）和血浆肾素活性。Logistic回归模型将 以鉴定预测临床终点的生物标志物。在目标2中，我们将使用下一代 测序、RT-qPCR和高通量代谢组学分析，以评估细胞外 miRNAs和代谢物。代谢组广泛关联研究（MWAS）和集合特征选择（EFS） 将用于识别强大的生物标志物，并开发严重COVID-19的预测模型。数据来自EFS 分析将输入到程序xMWAS，该程序将确定miRNA代谢组之间的连接性 网络和临床结果。 临床相关性：患有心血管疾病的退伍军人感染SARS-CoV-2的风险更高， 严重疾病进展。我们的团队拥有基础设施和方法，可以进行深入的，多方面的， 组学研究，以解决退伍军人与COVID-19的不良结果的预测因素，并确定表观遗传和 心脏代谢途径决定了对不良后果的敏感性。此外，由于50%的 亚特兰大退伍军人医疗中心的退伍军人是非洲裔美国人，我们处于独特的地位， 解决种族在严重COVID-19易感性中的作用。发现新的生物标志物和途径 与严重COVID-19相关的疾病对筛查、治疗和实施 早期个性化干预策略，以减轻不良后果。