Abstract
PURPOSE: Multiple cell types interact within the aortic wall to control development, homeostasis, and adaptation as well as to drive disease progression. Given the complexity of these interactions and their manifestations at the tissue level, there is a pressing need for a new class of computational models that integrate data across scales. METHODS: We meld logic-based cell signaling models of vascular smooth muscle cells, adventitial fibroblasts, and macrophages and couple this multi-cell model with a tissue level-constrained mixture model of aortic growth and remodeling. The coupled multi-scale model is parameterized using data from the literature and then specialized for the case of angiotensin II-induced hypertensive remodeling of the descending thoracic aorta in wild-type mice. RESULTS: We contrast important contributions of chemo- and mechano-stimulation of cell responses and identify critical roles of recruited macrophages in driving the non-homeostatic thickening of the adventitial layer that reduces biaxial wall stress below setpoint values. CONCLUSION: We show the utility of a multi-scale, multi-cell model in delineating effects of different chemo-mechanical stimuli in aortic remodeling in hypertension.