COVID19: Anti-SARS-CoV-2 Antibodies and Infection Severity

新的Covid-19病毒对0.2%至4%的感染者是致命的，老年男性受影响最严重 随着这一祸害，在80年内，15%的感染者会死亡，使美国退伍军人人口 尤其脆弱。了解这种致命的病理生理机制是至关重要的， 为了设计能够拯救生命的干预措施。MERS、SARS-CoV，以及现在新的人类Covid-19意味着 三种冠状病毒有可能成为全世界可怕的公共卫生问题;这 上一次也是最近一次的新冠肺炎疫情取得了成功。 针对这种病毒形成的一些抗体似乎加重了疾病的临床严重性， 使得免疫反应的具体细节对许多感染患者的死亡负责。我们 作为VA Merit支持研究人员探索抗原性的研究人员， 狼疮自身抗原的结构，导致我们的理论，EB病毒引起狼疮，这是一个 现在有令人信服的间接证据支持这一假设。我们建议将我们的经验应用于 探索抗Covid-19抗体反应的精细抗原特异性的细节，以便 了解哪些特定的抗体是危险的。我们提出两个假设： 假设1.将提供有关Covid-19抗体免疫反应的具体和详细知识， 用于阐明致病机制，预测疾病严重程度，设计疫苗， 选择治疗性等离子体，做出患者护理决策，告知人群流行病学， 确定感染动态，并在面对COVID-19时选择个人行为 流行病 假设2.抗Covid-19抗体精细抗原特异性将与临床相关 表现和感染严重程度。 我们提出两个目标： 目标1.开发和应用分析方法，以剖析针对共享的抗体形成的抗原特异性 和亚株特异性Covid-19抗原在自然人Covid-19感染中的作用。 目标2.分离和纯化针对主要表位的抗Covid-19抗体和任何特异性抗体， 与严重的肺部疾病有关 我们将使用蛋白质印迹、固相分析（ELISA）、表达30-mer氨基酸的噬菌体展示文库、 酸性肽，并合成重叠的Fmoc肽，以充分表征精细的特异性抗体 对新冠病毒的反应。我们将从退伍军人和其他人那里获得血浆和血清， 评估与临床结果的相关性。我们将分离个体特异性并描述其特征， 关于类型、同种型、糖基化和活性的性质。我们将进行假型分析， BSL 2中的完整库和单个抗体特异性，并进行中和确认试验， 与BSL 3设施合作。从这些研究中，我们希望了解如何识别可能 并为开发可能成功改善的方法提供线索 严重感染和预防严重疾病。

The new Covid-19 virus is deadly for 0.2% to 4% of people infected, with older men the most severely afflicted with this scourge, being mortal to ~15% of those infected over 80 years, making the US Veteran population especially vulnerable. It is critically important to understand the mechanisms of this lethal pathophysiology in order to design interventions that will save lives. MERS, SARS-CoV, and now the new human Covid-19 mean that three coronaviruses have threatened to become horrific public health problems for the entire world; this last and most recent one, Covid-19, has succeeded. Some of the antibodies formed against this virus appear to accentuate the clinical severity of disease, possibly making the specific details of the immune response responsible for the demise of many infected patients. We have had more than two decades of experience as VA Merit supported investigators exploring the antigenic structure of the lupus autoantigens, leading us to the theory that Epstein-Barr virus causes lupus, which is a hypothesis now supported by convincing circumstantial evidence. We propose to apply our experience to exploring the details of the fine antigenic specificity of the anti-Covid-19 antibody response in order to understand what specific antibodies are dangerous. We propose to explore two hypotheses: Hypothesis 1. Specific and detailed knowledge of antibody immune responses to Covid-19 will be useful for elucidating pathogenic mechanisms, predicting disease severity, designing vaccines, selecting therapeutic plasmas, making patient care decisions, informing population epidemiology, determining infection dynamics, and choosing individual behaviors in the face of the Covid-19 pandemic. Hypothesis 2. Anti-Covid-19 antibody fine antigenic specificity will correlate with clinical manifestations and infection severity. We propose two aims: Aim 1. Develop and apply assays to dissect the antigenic fine specificity of antibodies forming against shared and sub-strain specific Covid-19 antigens in the natural human Covid-19 infection. Aim 2. Isolate and purify anti-Covid-19 antibodies against the major epitopes and any specific antibodies that are associated with severe pulmonary disease. We will use Western blotting, solid phase assays (ELISAs), phage display libraries expressing 30-mer amino acid peptides, and synthesized overlapping fmoc peptides to fully characterize the fine specificity antibody response to the Covid-19 virus. We will obtain plasma and serum from Veterans and others which we will evaluate for correlates with clinical outcome. We will isolate individual specificities and characterize their properties with respect to type, isotype, glycosylation, and activity. We will perform pseudotype assays on whole repertoires and individual antibody specificities in BSL2 and test for confirmation with neutralization with collaborators with BSL3 facilities. From these studies we hope to learn how to identify Veterans who are likely to have a more severe illness and provide clues for developing approaches that could succeed in ameliorating infection severity and prevent severe disease.