Date of Award
2023
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Complex Systems and Data Science
First Advisor
Jason H. Bates
Abstract
Idiopathic pulmonary fibrosis (IPF) is a devastating, progressive and ultimately fatal interstitial lung disease of unknown etiology. Like most forms of fibrosis, it is thought to reflect an error in the homeostatic wound healing process, leading to excess scar tissue that impairs lung function. With few effective treatments, uncovering the pathogenesis of IPF may provide crucial information for improving outcomes. However, its elusive origin makes research with traditional methods in biology, such as cell and animal models, challenging. Here, we employ computational models to simulate the development of IPF and investigate mechanisms by which the disease begins and progresses.
IPF has many distinctive features that suggest important clues about its pathogenesis, such as primarily afflicting the older population. It also presents as spatially heterogeneous, starting in the basal, pleural regions. This gives the lung a “honeycomb” appearance on computed tomography (CT). Scar tissue stiffens the lung through deposition of extracellular matrix proteins, particularly collagen. It has also been shown that restructuring of the collagen fibers alone is sufficient to affect the lung in a similar manner. Individual collagen fibers become stiffer through internal and external cross-linking, further contributing to an aberrant phenotype.
Parsing out which factors are essential to pulmonary fibrogenesis is amenable to mathematical investigation. First, we developed and applied a local fractal analysis to quantify the reorganization of collagen structure. The method showed that pulmonary fibrosis is characterized by increased spatial complexity that is exacerbated by age. Second, we developed a mechanics-based model of the collagen and elastin network in an alveolar wall. This revealed that the normally wavy structure of collagen at low strain becomes less pronounced with fibrosis and age as a result of increased internal cross-linking. In turn, tissue stretching caused stress to percolate through the collagen network sooner in fibrotic compared to normal tissue. Finally, we investigated mechanisms that may explain how IPF propagates in its typical spatially heterogeneous way by developing a spatiotemporal agent-based model. Agents, representing profibrotic cells, interact with their matrix environment to cause tissue remodeling. We based the baseline matrix of the model on microCT images of the lung architecture obtained from healthy mouse lungs. When our agents randomly walk on the lung structure, the architecture biases them to visit areas with more tissue volume, leading to a heterogeneous buildup of dense tissue. We found that a large increase in the number of agents was required to generate a tissue distribution similar to that seen in fibrotic lungs.
These complementary modeling studies advance our understanding of the morphogenic processes involved in the pathogenesis of IPF at both mesoscopic and macroscopic scales. We anticipate that our novel models will be useful in predicting unforeseen protein and/or cell behaviors that will stimulate further investigation.
Language
en
Number of Pages
181 p.
Recommended Citation
Casey, Dylan Tyler, "Computational Models Of Extracellular Matrix Remodeling In Pulmonary Fibrosis" (2023). Graduate College Dissertations and Theses. 1777.
https://scholarworks.uvm.edu/graddis/1777
Included in
Applied Mathematics Commons, Biomedical Engineering and Bioengineering Commons, Systems Science Commons