School of Engineering, Brown University, Providence, Rhode Island, United States of America.
Department of Mechanical Engineering, Clemson University, Clemson, South Carolina, United States of America.
PLoS Comput Biol. 2022 Mar 7;18(3):e1009892. doi: 10.1371/journal.pcbi.1009892. eCollection 2022 Mar.
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.
新出现的临床证据表明，2019 年冠状病毒病（COVID-19）患者微血管中的血栓形成在决定疾病进展方面起着至关重要的作用。由于 SARS-CoV-2 的传染性，患者的新鲜血液样本仅限于进行体外实验研究。在此，我们采用一种新的多尺度多物理计算框架，使用来自 COVID-19 患者的数据对微血管中的病理性血栓形成进行预测建模。该框架无缝集成了血栓形成过程中的关键组成部分，包括血液动力学、凝血因子的传输和凝血动力学、血细胞力学和黏附动力学，从而使我们能够量化许多文献中报道的促血栓形成因素的贡献，例如停滞、血液凝血因子水平和活性的紊乱、内皮细胞和白细胞对 COVID-19 中微血栓形成的炎症反应。我们的模拟结果表明，在所考虑的凝血因子中，抗凝血酶和因子 V 在促进血栓形成方面发挥更突出的作用。我们的模拟还表明，白细胞向内皮细胞的募集加剧了血栓形成，并导致血流阻塞。此外，我们表明最近发现的流动血细胞簇可能是白细胞从血栓形成部位脱落的结果，这可能成为新血栓形成的核心。这些发现指向应进一步评估和优先考虑 COVID-19 患者抗血栓治疗的潜在靶点。总之，我们的计算框架为定量理解病理性血栓形成的机制提供了强大的工具，并为治疗 COVID-19 相关血栓形成的新治疗方法提供了新的思路。
