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

项目总结

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.