A COVID-19 Pulmonary Outcome Clinical Prediction Rule Using Epigenetics

项目摘要/摘要 虽然大多数感染SARS-CoV-2的患者病情轻微，但少数人进展为重度 肺部转归。新冠肺炎肺炎及其相关呼吸衰竭的发病机制仍在 人们对此知之甚少。与社区获得性肺炎患者不同，他们迅速发展为临床和 感染的放射学证据，新冠肺炎肺炎的患者从开始有几天的间隔 从感染症状到住院的放射学上明显的肺炎。预测哪些患者 最初出现轻微症状的患者与进展为 严重的肺部后果目前是不可能的。这是一个关键的知识鸿沟，因为这些患者 可以通过早期关键干预措施针对目标，以改善结果和保护有限的资源。这个 该项目的目标是模拟和验证一个结合了现有的、详细的 临床变量和表观遗传标记来自我们的电子病历数据仓库，以 制定新冠肺炎严重度临床预测规则(COPR)。中心假设是，在患者中 最初出现最轻微的症状，COPR将预测谁将保持最轻微的症状和 世卫组织将进展为严重的肺部后果。因此，具体目标包括：(1)确定临床 预测进展为严重新冠肺炎肺结局的变量和表观遗传标志物，以及(2) 在内部验证这一临床预测规则。这项研究将促进医疗资源的有效利用 通过在疾病病程早期识别感染者并预测严重的 在症状最轻微时期的肺部结局。通过这个项目，我将学习如何：1)开发 并验证临床决策规则；2)将组学应用于临床研究。这一组合临床- 表观遗传变量方法也可能有益于其他病毒的临床结果的预测 感染，并可能为下一次大流行进行改造、验证和部署。

PROJECT SUMMARY/ABSTRACT Although most SARS-CoV-2 infected patients develop mild illness, a minority progress to develop severe pulmonary outcomes. The pathogenesis of COVID-19 pneumonia and associated respiratory failure remains poorly understood. Unlike patients with community-acquired pneumonia, who rapidly develop clinical and radiologic evidence of infection, patients with COVID-19 pneumonia have a several-day interval from the start of infective symptoms to hospitalization with radiographically apparent pneumonia. Predicting which patients who initially present with mild symptoms will remain minimally symptomatic versus those who progress to severe pulmonary outcomes is currently impossible. This is a critical knowledge gap because these patients could be targeted with early critical interventions to improve outcomes and preserve limited resources. The objective of this project is to model and validate a clinical prediction rule that incorporates existing, detailed clinical variables and epigenetic markers derived from our electronic medical record data warehouse to develop the COVID-19 severity clinical prediction rule (COPR). The central hypothesis is that, in patients initially presenting with minimal symptoms, the COPR will predict who will remain minimally symptomatic and who will progress to severe pulmonary outcomes. The Specific Aims therefore include: (1) to identify clinical variables and epigenetic markers to predict progression to severe COVID-19 pulmonary outcomes, and (2) to internally validate this clinical prediction rule. This study will facilitate the efficient use of healthcare resources through the identification of infected individuals early in their disease course and prediction of severe pulmonary outcomes during periods of minimal symptoms. Through this project I will learn how to: 1) develop and validate clinical decision rules, and 2) apply `omics to clinical investigation. This combination clinical- epigenetic variable approach could also be beneficial for the prediction of clinical outcomes in other viral infections and may be remodeled, validated, and deployed for the next pandemic.