Exploring the relationship between hemodynamics and the immune microenvironment in carotid atherosclerosis: Insights from CFD and CyTOF technologies

Abstract

Carotid atherosclerosis is a major cause of stroke. Hemodynamic forces, such as shear stress and oscillatory shear, play an important role in the initiation and progression of atherosclerosis. The alteration of the immune microenvironment is the fundamental pathological mechanism by which diverse external environmental factors impact the formation and progression of plaques. However, Current research on the relationship between hemodynamics and immunity in atherosclerosis still lack of comprehensive understanding. In this study, we combined computational fluid dynamics (CFD) and Mass cytometry (CyTOF) technologies to explore the changes in the immune microenvironment within plaques under different hemodynamic conditions. Our results indicated that neutrophils were enriched in adverse flow environments. M2-like CD163+CD86+ macrophages were predominantly enriched in high WSS and low OSI environments, while CD163-CD14+ macrophages were enriched in low WSS and high OSI environments. Functional analysis further revealed T cell pro-inflammatory activation and dysregulation in modulation, along with an imbalance in M1-like/M2-like macrophages, suggesting their potential involvement in the progression of atherosclerotic lesions mediated by adverse flow patterns. Our study elucidated the potential mechanisms by which hemodynamics regulated the immune microenvironment within plaques, providing intervention targets for future precision therapies.

Keywords: CFD; Carotid atherosclerosis; CyTOF; hemodynamic; immune environment.

Figure 1.

(a) Carotid plaque-carrying vessels from 13 enrolled cases were reconstructed and simulated in vitro. The measured values of WSS and OSI were rendered on the reconstructed vascular model (The brighter areas indicate the sampled range of the distal Continued.measurement of the plaque). (b) Workflow of this study. Collection of single-cell suspensions from plaques and subsequent mass cytometry analysis. Grouping of the 13 enrolled patients based on measured WSS/OSI (detailed information of grouping in Supplementary Table 4). Comparative analysis of the composition differences in these specimens. (c) Two-dimensional T-SNE plot illustrating the dimensionality reduction results of FlowSOM clustering analysis in 13 plaques. (d) Stacked bar chart depicting the proportion of various immune cells in the 13 samples and (e) the spectral colors overlaid on the t-SNE plot illustrate the marker expression patterns of these 8 cell subsets.

Figure 2.

Comparative analysis of the 8 immune clusters under different hemodynamic conditions. (a–d) The analysis results under WSS grouping conditions. (e–h) The analysis results under OSI grouping conditions. (a and e) T-SNE plots illustrate the dimensional reduction results of the 8 immune cell clusters under different grouping conditions. (b and f) Stacked bar charts depict the Continued.composition of the 8 immune cell clusters in high and low hemodynamic parameter (WSS/OSI) groups (color rendering consistent with the T-SNE plots). (c and g) Box-scatter plots display the comparison of the proportions of the 8 immune clusters between high and low hemodynamic parameter groups (red asterisks indicate statistically significant differences). (d and h) Box-scatter plots show the comparison of the expression of functional molecules in the 8 immune cell clusters between high and low hemodynamic parameter groups (only results with statistically significant differences are displayed; complete comparative results are provided in Supplementary Figures 4 and 5).

Figure 3.

Distribution and functional characteristics of the identified 6 macrophage subgroups in the samples. (a) T-SNE plots illustrate the FloSOM clustering analysis results of macrophages in the 13 enrolled samples. (b) Doughnut charts depict the proportions of the identified 6 macrophage subgroups in the samples. (c) Heatmaps display the surface marker expression profiles of the 6 macrophage subgroups and (d) ridge plots illustrate the expression patterns of functional molecules in the 6 macrophage subgroups.

Figure 4.

Comparative analysis of the 6 macrophage subgroups under different hemodynamic conditions. (a–d) The analysis results of 6 macrophage subgroups under WSS grouping conditions. (e–h) The analysis results of 6 macrophage subgroups under OSI grouping conditions. (a and e) T-SNE plots illustrate the dimensionality reduction results of the 6 macrophage subgroups under different grouping conditions. (b and f) Stacked bar charts depict the composition of the 6 macrophage subgroups in the high blood flow parameter (WSS/OSI) group and low blood flow parameter (WSS/OSI) group (color-coding consistent with the T-SNE plots). (c and g) Box-scatter plots show the proportion of the 6 macrophage subgroups in the comparison between high and low blood flow parameter groups (red asterisks indicate statistically significant differences). (d and h) Box-scatter plots show the comparison of the expression of functional molecules in the 6 macrophage subgroups between high and low hemodynamic parameter groups (only results with statistically significant differences are displayed; complete comparative results are presented in Supplementary Figures 8 and 9).