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 COVID-19 (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.

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