Heart disease, strokes, and limb loss continue to lead mortality and morbidity. Despite advances in surgical and endovascular treatments, long-term success of these interventions remains limited. Researchers have applied a variety of approaches to modify neointimal hyperplasia and vascular remodeling in an effort to improve the outcomes;however, attempts have been largely ineffective due to incomplete understanding of the specific cause/effect links through which hemodynamic factors, biochemical mediators, and cellular effectors lead to an occlusive vascular phenotype after intervention. Prior research has focused almost exclusively on either the static isolated physical or biologic components. For instance, we confirmed that wall shear stress stands as a key regulator of vascular architecture. In parallel, we established that temporally distinct vessel wall inflammatory events (mediated by blood monocytes) predict long-term morphology. However, completely lacking is an understanding of the dynamic interplay between physical forces and cellular inflammatory elements that modulate local variations in wall remodeling, and ultimately success or failure of the intervention. Focusing on clinically relevant vein bypass grafting as a model system, this proposal will fuel the synergy of vascular biologists, engineers, and mathematicians who will employ systems biology approaches to the complex mechanisms of vascular adaptation. This established team will construct and optimize pioneering multi-scale models to understand the interplay of micro-scale physical and biologic forces in vein graft wall behavior. The proposed hypothesis driven model conceptualizes the process of vascular adaptation as two parallel, but interconnected processes. The global remodeling response is mediated through variations in the gene regulatory network (Specific Aim 1), while the focality of lesion development is modulated through the dynamics of monocyte homing to regions of altered flow (Specific Aim 2). The general approach of this proposal is the use of robust but validated computational algorithms for the development of each module. Interfaced with extensive in vivo experimental data, each module contributes a new structural integration level to the overall model. Upon compilation, the final model will utilize an iterative loop, employing a finite element computational technique (hemodynamic module) that drives a Bayesian network (gene regulatory module) and series of partial differential equations (monocyte kinetic module), with resulting outputs interfaced through a cellular automata to predict changes in tissue architecture, which feeds back into the hemodynamic module to initiate a new cycle. Structured to maintain spatial integrity, the underlying power of the predictive model is to examine the regional difference in disease progression in a complex three- dimensional geometry. This work not only provides direct clinical translation toward improved bypass graft durability, but most importantly it stands as a powerful contemporary application of rigorous systems biology approaches to understand and treat complex medical diseases.

Public Health Relevance

Heart attack and stroke continue to be the leading cause of mortality and morbidity in the United States. Available treatments, such as vein bypass surgery or angioplasty, currently provide only short-term improvements, and are prone to failure due to aggressive scar formation. The current proposal uses systems biology approaches to study the complex mechanisms of the vascular response to injury, providing a predictive model with application both as a research tool and in the care of patients.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1-BST-E (51))
Program Officer
Larkin, Jennie E
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Florida
Other Domestic Higher Education
United States
Zip Code
Garbey, Marc; Rahman, Mahbubur; Berceli, Scott A (2015) A Multiscale Computational Framework to Understand Vascular Adaptation. J Comput Sci 8:32-47
He, Yong; Fernandez, Chessy M; Jiang, Zhihua et al. (2014) Flow reversal promotes intimal thickening in vein grafts. J Vasc Surg 60:471-478.e1
Wang, Jianxin; Chen, Bo; Wang, Yaqun et al. (2013) Reconstructing regulatory networks from the dynamic plasticity of gene expression by mutual information. Nucleic Acids Res 41:e97
Garbey, Marc; Berceli, Scott A (2013) A dynamical system that describes vein graft adaptation and failure. J Theor Biol 336:209-20
Hwang, Minki; Garbey, Marc; Berceli, Scott A et al. (2013) Rule-based model of vein graft remodeling. PLoS One 8:e57822
Wang, Yaqun; Xu, Meng; Wang, Zhong et al. (2012) How to cluster gene expression dynamics in response to environmental signals. Brief Bioinform 13:162-74
Hwang, Minki; Berceli, Scott A; Garbey, Marc et al. (2012) The dynamics of vein graft remodeling induced by hemodynamic forces: a mathematical model. Biomech Model Mechanobiol 11:411-23
Li, Ning; McMurry, Timothy; Berg, Arthur et al. (2010) Functional clustering of periodic transcriptional profiles through ARMA(p,q). PLoS One 5:e9894
Jiang, Zhihua; Yu, Peng; Tao, Ming et al. (2009) Interplay of CCR2 signaling and local shear force determines vein graft neointimal hyperplasia in vivo. FEBS Lett 583:3536-40
Hwang, Minki; Garbey, Marc; Berceli, Scott A et al. (2009) Rule-Based Simulation of Multi-Cellular Biological Systems-A Review of Modeling Techniques. Cell Mol Bioeng 2:285-294

Showing the most recent 10 out of 11 publications