Evidence implicating roles of diverse genetic mutations in aortic disease continues to accumulate, and in many cases these mutations ultimately affect the mechanical functionality or structural integrity of the wall. Moreover, many mutations preferentially affect different layers (e.g., elastin-associated glycoproteins or smooth muscle actomyosin filaments within the media). The goal of this project is to quantify and compare effects of ten different mutations that predispose to aortic disease and affect medial versus adventitial properties. This information, in turn, will provide important new insight into deviations from the different mechanobiological homeostatic targets of the media and adventitia and possibly motivate novel therapeutic approaches. The specific goals of this R03 project are, therefore, to mine and interpret an extensive data base in our laboratory on the biaxial mechanical behavior of the murine aorta (i) to delineate, for the first time, differences in medial and adventitial load carrying in diverse genetically modified mouse models and (ii) to inform a novel growth and remodeling computational model that can be used to understand better how the aorta attempts to compensate mechanically and structurally given specific genetic mutations. Toward this end, our Specific Aims are: (1) Use our recently proposed novel biomechanical modeling approach to quantify and compare biaxial stresses and associated mechanical properties of the aortic media and adventitia from ten mouse models having mutations in genes that encode: elastin, fibrillin-1, fibulin-5, collagen III, collagen I, thrombo- spondin-2, alpha smooth muscle actin, smooth muscle myosin heavy chain, transforming growth factor beta receptor II, and latent transforming growth factor binding protein 3, all in comparison to two wild type controls (pure and mixed backgrounds), and (2) Extend, inform, and validate a novel thick-walled growth and remodeling model that we developed to understand constituent-specific contributions to arterial mechanics, but which now will be used to delineate better the layer-specific compensatory mechanisms that either enable aortic adaptation or lead to aortic mal-adaptation, particularly vulnerability to aortic dissection and rupture. This proposal is submitted under the R03 mechanism because it is a small, self-contained research project that will rely on a secondary analysis of existing data and yet result in the development of [a new] research methodology. Note that this proposal is not submitted under the R21 mechanism because we do not view it as high risk. Rather, given our extensive experience with model building and diverse aspects of mouse mechanics and mechanobiology, we do not anticipate any technical obstacles. Rather, we simply need modest support and time to develop, inform, and validate what we feel are much needed, highly innovative models of aortic biomechanics that will better reveal the genetic basis of aortic adaptivity versus evolving structural vulnerability.

Public Health Relevance

Mounting evidence reveals that diverse genetic mutations predispose to early vascular aging, hypertension, and aortic aneurysms and dissections, among other conditions. Underlying these disease processes are differential changes in the biomechanics of the two primary layers of the aortic wall. This project will develop a unique computational model to quantify, for the first time, how specific mutations affect these two layers and thus the overall mechanical functionality and structural vulnerability of the aortic wall.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Small Research Grants (R03)
Project #
5R03EB021430-02
Application #
9208773
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Peng, Grace
Project Start
2016-02-15
Project End
2018-01-31
Budget Start
2017-02-01
Budget End
2018-01-31
Support Year
2
Fiscal Year
2017
Total Cost
$64,981
Indirect Cost
$19,981
Name
Yale University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
043207562
City
New Haven
State
CT
Country
United States
Zip Code
06520
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Bellini, C; Bersi, M R; Caulk, A W et al. (2017) Comparison of 10 murine models reveals a distinct biomechanical phenotype in thoracic aortic aneurysms. J R Soc Interface 14:
Bellini, C; Caulk, A W; Li, G et al. (2017) Biomechanical Phenotyping of the Murine Aorta: What Is the Best Control? J Biomech Eng 139: