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

目的：来自新冠肺炎大流行的新数据表明，男性和非裔美国人患上更高的 死亡率和心脏代谢危险因素，包括肥胖、糖尿病和高血压，聚集在以下患者中 出现SARS-CoV-2感染的不良后果。退伍军人尤其容易受到 新冠肺炎由于心脏代谢危险因素的患病率很高。然而，并不是所有的退伍军人 新冠肺炎经历了严重的疾病，迫切需要确定新的分子途径 新冠肺炎的潜在风险和韧性。我们团队之前的工作和初步研究已经 证明了靶向蛋白质组学、代谢组学和miRNA组学可以识别新的生物标记物和 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 阐明与严重新冠肺炎的风险和复原力相关的新的生物标志物和途径。 研究计划：在目标1中，我们将比较住院患者中途径特异性生物标记物的表达 重度新冠肺炎伴这些生物标记物表达的患者中未发展为重度新冠肺炎。 反映肾素-血管紧张素-醛固酮系统激活的通路特异性生物标志物 炎症、氧化应激、免疫激活、血栓形成、心肌损伤和拉伸 评估过了。严重疾病的主要终点是IL-6水平或肌钙蛋白I水平的病理性升高。 次要终点将用于机械通风、充血性心力衰竭、更换沙发 得分和死亡。在目标2中，我们将评估相同的两个细胞外miRNA和代谢组谱 住院新冠肺炎患者组及测定miRNA和代谢物的差异表达 在这两组人之间。随后，我们将检查miRNA-代谢组网络之间的连通性 通过对差异表达的综合分析，确定新冠肺炎患者的临床终点 MiRNAs和代谢物，这将确定与严重感染相关的代谢途径。 方法：拟议的研究将分析新冠肺炎的不明身份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 目前存储新冠肺炎常规实验室检测的残留血浆和血清的生物库 病人。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)的水平 HsCRP(炎症)、hsTnI(心肌损伤)、BNP(心肌拉伸)、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回归建模将 以确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评估细胞外的表达 MiRNA和代谢物。代谢组广谱关联研究和集成特征选择 将被用来识别强大的生物标志物，并开发严重新冠肺炎的预测模型。来自EFS的数据 分析将输入到xMwas程序中，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， 严重的疾病进展。我们的团队有基础设施和方法来进行深入的、多方面的 针对新冠肺炎退伍军人不良结局预测因素的组学研究，并确定表观遗传学和 心脏代谢途径决定了对不良结果的易感性。此外，因为50%的 退伍军人在亚特兰大退伍军人医疗中心退伍军人是非裔美国人，我们处于独特的地位 阐述种族在严重新冠肺炎易感性中的作用。新的生物标志物和途径的发现 与严重新冠肺炎相关的疾病对筛查、治疗和实施 减少不良后果的早期个体化干预策略。

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.