Department of Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts.
School of Engineering, Brown University, Providence, Rhode Island; School of Chemical, Materials and Biomedical Engineering, University of Georgia, Athens, Georgia.
Biophys J. 2022 Sep 20;121(18):3309-3319. doi: 10.1016/j.bpj.2022.08.031. Epub 2022 Aug 27.
Microthrombi and circulating cell clusters are common microscopic findings in patients with coronavirus disease 2019 (COVID-19) at different stages in the disease course, implying that they may function as the primary drivers in disease progression. Inspired by a recent flow imaging cytometry study of the blood samples from patients with COVID-19, we perform computational simulations to investigate the dynamics of different types of circulating cell clusters, namely white blood cell (WBC) clusters, platelet clusters, and red blood cell clusters, over a range of shear flows and quantify their impact on the viscosity of the blood. Our simulation results indicate that the increased level of fibrinogen in patients with COVID-19 can promote the formation of red blood cell clusters at relatively low shear rates, thereby elevating the blood viscosity, a mechanism that also leads to an increase in viscosity in other blood diseases, such as sickle cell disease and type 2 diabetes mellitus. We further discover that the presence of WBC clusters could also aggravate the abnormalities of local blood rheology. In particular, the extent of elevation of the local blood viscosity is enlarged as the size of the WBC clusters grows. On the other hand, the impact of platelet clusters on the local rheology is found to be negligible, which is likely due to the smaller size of the platelets. The difference in the impact of WBC and platelet clusters on local hemorheology provides a compelling explanation for the clinical finding that the number of WBC clusters is significantly correlated with thrombotic events in COVID-19 whereas platelet clusters are not. Overall, our study demonstrates that our computational models based on dissipative particle dynamics can serve as a powerful tool to conduct quantitative investigation of the mechanism causing the pathological alterations of hemorheology and explore their connections to the clinical manifestations in COVID-19.
微血栓和循环细胞簇是不同病程阶段的 2019 冠状病毒病(COVID-19)患者的常见微观发现,这表明它们可能是疾病进展的主要驱动因素。受 COVID-19 患者血液样本的近期流动成像细胞术研究的启发,我们进行了计算模拟,以研究不同类型的循环细胞簇(即白细胞(WBC)簇、血小板簇和红细胞簇)在不同剪切流下的动力学,并量化它们对血液粘度的影响。我们的模拟结果表明,COVID-19 患者中纤维蛋白原水平的升高可以促进在相对较低的剪切速率下形成红细胞簇,从而升高血液粘度,这种机制也会导致其他血液疾病(如镰状细胞病和 2 型糖尿病)的粘度升高。我们进一步发现,WBC 簇的存在也可能加重局部血液流变学的异常。特别是,随着 WBC 簇的增大,局部血液粘度的升高程度会增大。另一方面,血小板簇对局部流变学的影响被发现可以忽略不计,这可能是由于血小板的尺寸较小。WBC 和血小板簇对局部血液流变学的影响的差异为 COVID-19 中与血栓事件显著相关的 WBC 簇数量而血小板簇不相关的临床发现提供了一个有说服力的解释。总的来说,我们的研究表明,我们基于耗散粒子动力学的计算模型可以作为一种强大的工具,对导致血液流变学病理改变的机制进行定量研究,并探索它们与 COVID-19 临床表现的联系。