BIOMARKERS OF COAGULATION, ENDOTHELIAL DYSFUNCTION, AND FIBRINOLYSIS IN PATIENTS WITH COVID-19

Abstract

Immunothrombosis and coagulopathy in lung microvasculature may lead to lung injury and disease progression in severe COVID-19. However, the mechanism that leads to decompensation and death for some patients, thus delineating them from patients who recover and survive, is poorly understood. We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential. Our study has explored four different cohorts: 1) our pilot cohort, 2) COVID-BEACONS study cohort, 3) CanCOV study cohort and 4) ACTIV-4A trial cohort. The patient plasmas from these samples were quantified using 1) ELISAs for plasminogen, soluble thrombomodulin (sTM), plasminogen activator inhibitor-1 (PAI-1), α2-antiplasmin (A2AP), thrombin antithrombin complex (TAT), D-dimer, thrombin-activatable fibrinolysis inhibitor (TAFI), and fibrinogen, and 2) in-house functional assays for clot lysis times and activated TAFI (TAFIa) levels. Biomarker values were log-transformed and linear mixed effects models were used to compare trajectories in ICU and ward patients compared to outpatients from date of symptom onset. Our pilot cohort showed that sTM, PAI-1, plasminogen and clot lysis times have predictive ability for mortality. In order to validate these findings, we explored the other three cohorts. The COVID-BEACONS cohort confirmed that plasminogen is associated with death and showed that fibrinogen and TAFI levels also predicted mortality in the COVID-19 patients. In the CanCOV study cohort, D-dimer and sTM antigen levels showed the strongest associations with moderate and severe COVID-19 compared to mild disease. PAI-1, plasminogen, TAFIa, and fibrinogen may additionally be useful in identifying patients who become critically ill. Lastly, the ACTIV-4A trial cohort showed an increase in PAI-1, sTM and TAFIa levels in COVID-19 outpatients, whereas a longitudinal decrease in the antigen levels of fibrinogen and A2AP was observed. The data from the cohorts needs to be normalized using clinical data and symptom onset data, and then used to validate the findings of our pilot cohort. Once that is achieved, our study has the potential to identify biomarkers that can predict which patients are likely to be severe and worsen over time, which could lead to early treatment and better chance of survival.