ABSTRACT
Introduction: Circulating Cellular Clusters (CCCs) have been studied in the context of cancer;however, CCCs in other inflammatory conditions, such as COVID-19, have not been explored. Hypothesis: CCC phenotypes play a role in immunothrombosis and in the development of adverse events. Methods: Blood samples were collected from patients with a positive SARS-CoV2 PCR treated at the Massachusetts General Hospital. Imaging flow cytometry was used to characterize CCCs, including: platelet-leukocyte aggregates (PLAs), leukocyte clusters (LCs) and platelet-erythrocyte aggregates (PEAs) (Fig1A). CCC phenotypes were compared with controls and were correlated with clinical outcomes. CCCs identified to be significant were used to guide a computational model investigating the mechanism of CCC formation and their behavior in circulation (Fig1C). Results: Forty-six COVID-19 and 12 control samples were analyzed. Statistically significant positive correlations were identified between CCCs and clinical outcomes in patients with COVID19 (Fig1B). Using these data as inputs, computational simulations illustrated that CCCs may form in the circulation and be recruited by existing thrombi and sites of inflammation, or may detach from thrombogenic sites (Fig1D). Conclusions: CCCs are correlated with the development of significant clinical outcomes and cluster phenotypes appear to be associated with specific outcomes. CCCs may form de novo in the circulation or via the detachment from a thrombus. These CCCs may subsequently attach to a second thrombus downstream or serve as their own nidus for thrombus development, resulting in vessel lumen occlusion. Computational modeling serves as a powerful tool for the exploration of the pathophysiological mechanism by which CCCs contribute to thrombus formation. These findings may serve as novel biomarkers and aid in the identification of new drug targets for immunothrombotic complications in severe inflammatory conditions.
ABSTRACT
Introduction: Severe COVID-19 has been associated with aberrant coagulation factor activities, particularly in patients with a thrombotic event (TE). Management of anticoagulant is critical in the care of hospitalized patients with COVID-19.Hypothesis: Evaluation of a point-of-care (POC), functional, clot-time-based coagulation test to detect the anticoagulant effect of therapeutic unfractionated heparin (UFH) in hospitalized SARS-CoV-2-positive patients who developed a TE. Methods: An IRB-approved analysis of 36 citrated plasma specimens from 26 SARS-CoV-2-positive patients and 10 matched negative controls was performed. A Clotting Time Score (CTS), a measure of factor-specific inhibition (i.e. anticoagulant activity), was derived for each patient. CTS results were compared with traditional coagulation tests. Five UFH COVID-19 samples with low CTS scores (<10) were spiked with uniform dosing of UFH, low molecular weight heparin (LMWH), apixaban, or argatroban and retested to assess anticoagulation response. Results: The CTS detected subtherapeutic UFH anticoagulation levels more frequently in COVID-19 cases compared with controls (76% vs. 17%). Prothrombin Times, activated Partial Thromboplastin Times, anti-Xa levels, and antithrombin activity did not correlate with each other or with the CTS in the COVID-19 samples. CTS correlated with both FV and Factor X activity (R =0.49, Spearman R=-0.68), which form the prothrombinase complex. The CTS was 94% sensitive and 67% specific for the occurrence of TEs in patients on UFH. CTS demonstrated a consistent anticoagulant response only to argatroban (100%) compared with other anticoagulants (60%). Conclusions: The CTS, generated using a novel, low-volume, rapid POC coagulation test is a strong indicator of the therapeutic effect of UFH anticoagulation in COVID-19 patients and may provide a predictive measure of TEs potentially occurring from anticoagulation resistance.
ABSTRACT
Background : COVID-19 triggers a pro-inflammatory and prothrombotic state. The role of circulating cellular clusters in the setting of COVID-19 remains unclear. Aims : This study explores the phenotype of circulating clusters and their potential relationship with clinical outcomes in COVID-19 patients. Methods : Blood samples were collected between July -August 2020 from patients with a positive SARS-CoV2 PCR treated at a large academic medical center. Imaging flow cytometry was used to detect various circulating cellular clusters, including: platelet (plt)-leukocyte aggregates (PLAs: 1 leukocyte + plt), leukocyte clusters (LC: ≥2 leukocytes ± any other cell) and platelet-erythrocyte aggregates (PEAs: ≥1 erythrocyte + plt) (Figure 1). Cluster phenotypes were compared in patients with and without COVID-19 and were retrospectively correlated with clinical outcomes. Results : Forty-six COVID and 12 non-COVID samples were analyzed. Patients with COVID-19 had higher circulating PEAs (2.58% ± 0.12% vs 1.41% ± 0.72%, P = .001) and manually-counted PLAs (0.15% ± 0.11% vs. 0.06% ± 0.03% P = .007) compared to healthy controls. Table 1 shows the relationship between specific populations of clusters and clinical outcomes in patients with COVID-19. The presence of LCs, in particular, significantly correlated with thrombotic events ( P = 0.006), whereas PLAs and PEAs did not ( P = 0.73 and P = 0.9, respectively). Blood type was also correlated to LCs ( P = 0.021), with Type O having the least LCs, followed by Types A, AB and B. Conclusions : Circulating cellular clusters are correlated with significant clinical outcomes and cluster phenotypes appear to be associated with specific outcomes, including thrombotic events. These immuno-thrombotic complexes may play a significant role in the development of thrombosis and resultant end-organ damage. Further study of the role of the cellular component in COVID-19 may lead to the development of prediction models and help identify novel drug targets for inflammation-related thrombosis.