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PLoS Comput Biol . Multiphysics and multiscale modeling of microthrombosis in COVID-19

tetano

Editor, Senior Moderator
PLoS Comput Biol


. 2022 Mar 7;18(3):e1009892.
doi: 10.1371/journal.pcbi.1009892. eCollection 2022 Mar.
Multiphysics and multiscale modeling of microthrombosis in COVID-19


He Li[SUP] 1 [/SUP], Yixiang Deng[SUP] 1 [/SUP], Zhen Li[SUP] 2 [/SUP], Ander Dorken Gallastegi[SUP] 3 [/SUP], Christos S Mantzoros[SUP] 4 [/SUP], Galit H Frydman[SUP] 5 6 [/SUP], George E Karniadakis[SUP] 1 7 [/SUP]



Affiliations

Abstract

Emerging clinical evidence suggests that thrombosis in the microvasculature of patients with Coronavirus disease 2019 (COVID-19) plays an essential role in dictating the disease progression. Because of the infectious nature of SARS-CoV-2, patients' fresh blood samples are limited to access for in vitro experimental investigations. Herein, we employ a novel multiscale and multiphysics computational framework to perform predictive modeling of the pathological thrombus formation in the microvasculature using data from patients with COVID-19. This framework seamlessly integrates the key components in the process of blood clotting, including hemodynamics, transport of coagulation factors and coagulation kinetics, blood cell mechanics and adhesive dynamics, and thus allows us to quantify the contributions of many prothrombotic factors reported in the literature, such as stasis, the derangement in blood coagulation factor levels and activities, inflammatory responses of endothelial cells and leukocytes to the microthrombus formation in COVID-19. Our simulation results show that among the coagulation factors considered, antithrombin and factor V play more prominent roles in promoting thrombosis. Our simulations also suggest that recruitment of WBCs to the endothelial cells exacerbates thrombogenesis and contributes to the blockage of the blood flow. Additionally, we show that the recent identification of flowing blood cell clusters could be a result of detachment of WBCs from thrombogenic sites, which may serve as a nidus for new clot formation. These findings point to potential targets that should be further evaluated, and prioritized in the anti-thrombotic treatment of patients with COVID-19. Altogether, our computational framework provides a powerful tool for quantitative understanding of the mechanism of pathological thrombus formation and offers insights into new therapeutic approaches for treating COVID-19 associated thrombosis.
 
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