An agent-based model of cardiac allograft vasculopathy: toward a better understanding of chronic rejection dynamics

Frontiers in Bioengineering and Biotechnology

Bioengineering and Biotechnology

Xian C. Li¹  Stefano Casarin²  Anna Corti³  Diego Gallo⁴  Claudio Chiastra⁴  Elisa Serafini⁵ 

[1] Immunobiology and Transplant Science Center, Houston Methodist Hospital, Houston, TX, United States;Department of Surgery, Weill Cornell Medical College of Cornell University, New York, NY, United States;Department of Surgery, Houston Methodist Hospital, Houston, TX, United States;LaSIE, UMR 7356 CNRS, La Rochelle Université, La Rochelle, France;Center for Precision Surgery, Houston Methodist Research Institute, Houston, TX, United States;Department of Surgery, Houston Methodist Hospital, Houston, TX, United States;Laboratory of Biological Structure Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, Politecnico di Milano, Milan, Italy;PolitoMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy;PolitoMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy;LaSIE, UMR 7356 CNRS, La Rochelle Université, La Rochelle, France;Center for Precision Surgery, Houston Methodist Research Institute, Houston, TX, United States;

关键词: heart transplant;    chronic rejection;    cardiac allograft vasculopathy;    arterial wall remodeling;    coronary artery;    computational model;    agent-based modeling;    sensitivity analysis;   

DOI  :  10.3389/fbioe.2023.1190409

 received in 2023-03-20, accepted in 2023-08-17,  发布年份 2023

来源: Frontiers

【 摘 要 】

Cardiac allograft vasculopathy (CAV) is a coronary artery disease affecting 50% of heart transplant (HTx) recipients, and it is the major cause of graft loss. CAV is driven by the interplay of immunological and non-immunological factors, setting off a cascade of events promoting endothelial damage and vascular dysfunction. The etiology and evolution of tissue pathology are largely unknown, making disease management challenging. So far, in vivo models, mostly mouse-based, have been widely used to study CAV, but they are resource-consuming, pose many ethical issues, and allow limited investigation of time points and important biomechanical measurements. Recently, agent-based models (ABMs) proved to be valid computational tools for deciphering mechanobiological mechanisms driving vascular adaptation processes at the cell/tissue level, augmenting cost-effective in vivo lab-based experiments, at the same time guaranteeing richness in observation time points and low consumption of resources. We hypothesize that integrating ABMs with lab-based experiments can aid in vivo research by overcoming those limitations. Accordingly, this work proposes a bidimensional ABM of CAV in a mouse coronary artery cross-section, simulating the arterial wall response to two distinct stimuli: inflammation and hemodynamic disturbances, the latter considered in terms of low wall shear stress (WSS). These stimuli trigger i) inflammatory cell activation and ii) exacerbated vascular cell activities. Moreover, an extensive analysis was performed to investigate the ABM sensitivity to the driving parameters and inputs and gain insights into the ABM working mechanisms. The ABM was able to effectively replicate a 4-week CAV initiation and progression, characterized by lumen area decrease due to progressive intimal thickening in regions exposed to high inflammation and low WSS. Moreover, the parameter and input sensitivity analysis highlighted that the inflammatory-related events rather than the WSS predominantly drive CAV, corroborating the inflammatory nature of the vasculopathy. The proof-of-concept model proposed herein demonstrated its potential in deepening the pathology knowledge and supporting the in vivo analysis of CAV.

【 授权许可】

Unknown   
Copyright © 2023 Serafini, Corti, Gallo, Chiastra, Li and Casarin.