RESUMEN
BACKGROUND: Immunothrombosis and coagulopathy in the lung microvasculature may lead to lung injury and disease progression in coronavirus disease 2019 (COVID-19). We aim to identify biomarkers of coagulation, endothelial function, and fibrinolysis that are associated with disease severity and may have prognostic potential. METHODS: We performed a single-center prospective study of 14 adult COVID-19(+) intensive care unit patients who were age- and sex-matched to 14 COVID-19(-) intensive care unit patients, and healthy controls. Daily blood draws, clinical data, and patient characteristics were collected. Baseline values for 10 biomarkers of interest were compared between the three groups, and visualized using Fisher's linear discriminant function. Linear repeated-measures mixed models were used to screen biomarkers for associations with mortality. Selected biomarkers were further explored and entered into an unsupervised longitudinal clustering machine learning algorithm to identify trends and targets that may be used for future predictive modelling efforts. RESULTS: Elevated D-dimer was the strongest contributor in distinguishing COVID-19 status; however, D-dimer was not associated with survival. Variable selection identified clot lysis time, and antigen levels of soluble thrombomodulin (sTM), plasminogen activator inhibitor-1 (PAI-1), and plasminogen as biomarkers associated with death. Longitudinal multivariate k-means clustering on these biomarkers alone identified two clusters of COVID-19(+) patients: low (30%) and high (100%) mortality groups. Biomarker trajectories that characterized the high mortality cluster were higher clot lysis times (inhibited fibrinolysis), higher sTM and PAI-1 levels, and lower plasminogen levels. CONCLUSIONS: Longitudinal trajectories of clot lysis time, sTM, PAI-1, and plasminogen may have predictive ability for mortality in COVID-19.
Asunto(s)
COVID-19 , Fibrinólisis , Adulto , Biomarcadores , Enfermedad Crítica , Tiempo de Lisis del Coágulo de Fibrina , Humanos , Estudios Longitudinales , Inhibidor 1 de Activador Plasminogénico , Estudios Prospectivos , SARS-CoV-2 , Activador de Tejido PlasminógenoRESUMEN
IMPORTANCE: Coronavirus disease 2019 patients have an increased risk of thrombotic complications that may reflect immunothrombosis, a process characterized by blood clotting, endothelial dysfunction, and the release of neutrophil extracellular traps. To date, few studies have investigated longitudinal changes in immunothrombosis biomarkers in these patients. Furthermore, how these longitudinal changes differ between coronavirus disease 2019 patients and noncoronavirus disease septic patients with pneumonia are unknown. OBJECTIVES: In this pilot observational study, we investigated the utility of immunothrombosis biomarkers for distinguishing between coronavirus disease 2019 patients and noncoronavirus disease septic patients with pneumonia. We also evaluated the utility of the biomarkers for predicting ICU mortality in these patients. DESIGN SETTING AND PARTICIPANTS: The participants were ICU patients with coronavirus disease 2019 (n = 14), noncoronavirus disease septic patients with pneumonia (n = 19), and healthy age-matched controls (n = 14). MAIN OUTCOMES AND MEASURES: Nine biomarkers were measured from plasma samples (on days 1, 2, 4, 7, 10, and/or 14). Analysis was based on binomial logit models and receiver operating characteristic analyses. RESULTS: Cell-free DNA, d-dimer, soluble endothelial protein C receptor, protein C, soluble thrombomodulin, fibrinogen, citrullinated histones, and thrombin-antithrombin complexes have significant powers for distinguishing coronavirus disease 2019 patients from healthy individuals. In comparison, fibrinogen, soluble endothelial protein C receptor, antithrombin, and cell-free DNA have significant powers for distinguishing coronavirus disease 2019 from pneumonia patients. The predictors of ICU mortality differ between the two patient groups: soluble thrombomodulin and citrullinated histones for coronavirus disease 2019 patients, and protein C and cell-free DNA or fibrinogen for pneumonia patients. In both patient groups, the most recent biomarker values have stronger prognostic value than their ICU day 1 values. CONCLUSIONS AND RELEVANCE: Fibrinogen, soluble endothelial protein C receptor, antithrombin, and cell-free DNA have utility for distinguishing coronavirus disease 2019 patients from noncoronavirus disease septic patients with pneumonia. The most important predictors of ICU mortality are soluble thrombomodulin/citrullinated histones for coronavirus disease 2019 patients, and protein C/cell-free DNA for noncoronavirus disease pneumonia patients. This hypothesis-generating study suggests that the pathophysiology of immunothrombosis differs between the two patient groups.
RESUMEN
BACKGROUND: Thrombin-activated platelets can promote fibrinolysis by binding plasminogen in a fibrinogen-dependent manner and enhancing its activation by tissue-type plasminogen activator (t-PA). Whether t-PA also binds to activated platelets and the mechanism for regulation of platelet-dependent fibrinolysis remain unknown. OBJECTIVES: Determine the mechanism of plasminogen and t-PA binding on thrombin-activated platelets and its regulation by activated thrombin-activatable fibrinolysis inhibitor (TAFIa). METHODS: Plasminogen and t-PA binding with or without TAFIa treatment was quantified using flow cytometry. Plasmin generation on platelets was quantified using a plasmin-specific substrate. Mass spectrometry analyses identified fibrinogen as a potential target of TAFIa. Thrombus formation was studied in mice lacking fibrinogen (Fg-/- ) using intravital microscopy. RESULTS: Plasminogen and t-PA bind to platelets activated by thrombin but not by other agonists, including protease-activated receptor agonists (PAR-AP). Plasminogen binds via its kringle domains because ε-aminocaproic acid eliminates binding, whereas t-PA binds via its finger and kringle domains. Plasminogen binding is fibrinogen-dependent because it is abolished on (a) Fg-/- platelets, and (b) thrombi in Fg-/- mice. Binding requires thrombin-mediated fibrinogen modification because addition of batroxobin to PAR-AP activated platelets has no effect on plasminogen binding but induces t-PA binding. TAFIa reduces plasminogen and t-PA binding to thrombin-activated platelets and attenuates plasmin generation in a concentration-dependent manner. Mass spectrometry identified K556 on the fibrinogen alpha-chain as a potential thrombin cleavage site that generates a TAFIa sensitive C-terminal lysine residue. CONCLUSION: These findings provide novel mechanistic insights into how platelets activated by thrombin at sites of vascular injury can influence fibrinolysis.