Prediction of Major Adverse Kidney Events and Recovery (Pred-MAKER) in COVID-19 Patients

项目总结 主要的肾脏不良事件(MAK)在新冠肺炎患者中很常见，尤其是在 美国。我们来自西奈山的数据显示，大约40%的住院患者患上了急性肾脏 损伤(AKI)；20%的患者需要肾脏替代治疗，以及经历过 新冠肺炎相关急性心肌梗死的发生率是非急性心肌梗死患者的数倍。此外，我们已经看到， 与非COVID AKI相比，未恢复率也明显更高， 强调SARS-CoV-2相关肾脏损害的潜在长期影响。我们打算利用 在西奈山启动的高度协调的组织和生物量收集机器 卫生系统。作为危机中心最大的医院系统，西奈山治疗和 出院近万名新冠肺炎患者，创建中央IRB审批和数据协调系统 在新成立的西奈山COVID信息学中心的支持下。作为生物制品的一部分， 临床资料整理工作，我们已同意并取得血、尿或有临床指征的肾活检。 入院时来自700多名患者的样本。 使用这些样本，我们建议(1)使用多管齐下的方法来确定 与Make相关联；(2)开发基于机器学习的预测算法 多重生物标记物的表达水平和临床指标；以及，(3)确定 结合SARS-CoV-2阳性患者多组学问诊负责冠状病毒相关性AKI 尿液和肾脏活检以及体外原发近端细胞的时间依赖性转录特征 肾小管细胞。 首先，我们的结果将立即转化为结果，这将有助于将临床努力集中在HIGH 更快地对高危患者和低风险患者进行分诊。此外，我们的建议将有助于增进理解 导致新冠肺炎独特的肾脏损伤特征的复杂疾病机制，并可能导致 开发新的生物标志物和治疗药物，这些药物可能在冠状病毒感染后的临床中被证明是有益的 关心。我们严格的方法是创新的，并得到已建立的补充分析的支持。我们有 组建了一支经验丰富的多学科团队，包括生物工程师、肾病学家、基础科学家、 信息学家和病毒学家，将有助于改善对肾脏结果图景的理解 在新冠肺炎住院期间。

PROJECT SUMMARY Major adverse kidney events (MAKE) are common in individuals hospitalized with COVID-19, particularly in the United States. Our data from Mount Sinai show that ~40% of hospitalized patients develop acute kidney injury (AKI); 20% of those need renal replacement therapy, and the mortality rate in patients that experience COVID-19 associated AKI is several-fold greater than patients without AKI. Furthermore, we have seen that the rate of non-recovery is also significantly higher compared to those observed in non-COVID AKI, highlighting the potential long-term effects of SARS-CoV-2-associated kidney damage. We propose to utilize the highly coordinated tissue and biospecimen collection machinery that has been initiated at the Mount Sinai Health System. As the largest hospital system at the epicenter of the crisis, Mount Sinai treated and discharged nearly 10,000 COVID-19 patients and created a central IRB approval and data coordination system under the auspices of the newly formed Mount Sinai COVID Informatics Center. As part of biospecimen and clinical data collation efforts, we have consented and obtained blood, urine or clinically indicated kidney biopsy samples from over 700 patients at the time of admission. Using these samples, we propose (1) to use a multipronged approach to determine the biomarkers that are associated with MAKE; (2) to develop a machine learning-based predictive algorithm using a combination of multiplexed biomarker expression levels and clinical metrics; and, (3) to determine cellular pathways that are responsible for COVID-associated AKI by combining multiomics interrogation of SARS-CoV-2 positive patient urine and kidney biopsies as well as the time-dependent transcriptomic signatures of in vitro primary proximal tubule cells. First, our results will have an immediate translational outcome, which will help focus clinical efforts on high risk patients and triage low risk patients quicker. In addition, our proposal will lead to improved understanding of the complex disease mechanisms that cause the unique kidney injury signatures in COVID-19 and may lead to development of novel biomarkers and therapeutics that may prove beneficial during post-COVID clinical care. Our rigorous approach is innovative, and it is supported by established complementary assays. We have assembled an experienced multidisciplinary team encompassing bioengineers, nephrologists, basic scientists, informaticians and virologists that will help improve the understanding of the landscape of kidney outcomes during COVID-19 hospitalizations.