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Murine Surgical Model of Topical Elastase Induced Descending Thoracic Aortic Aneurysm
Published on: August 24, 2019
A multiscale computational model of ascending thoracic aortic aneurysm development in Marfan syndrome for in silico
Laurens Jansen1, Lauranne Maes1,2, Peter Verbrugghe3
1Division of Biomechanics, Department of Mechanical Engineering, KU Leuven, Leuven, Belgium.
Abstract:
Marfan syndrome (MFS) is a multisystemic connective tissue disorder caused by pathogenic variants of the gene encoding fibrillin-1, an important glycoprotein of the extracellular matrix. Among its diverse symptoms, the development of an ascending thoracic aortic aneurysm (ATAA) is the most concerning. An ATAA can fail due to dissection or rupture, both associated with substantial morbidity and mortality. Therefore, MFS patients typically receive medical treatment to slow aneurysm progression and reduce the risk of failure. However, the cellular mechanisms underlying ATAA development in MFS remain incompletely understood, reflected in suboptimal medical treatment options. To address this, we introduce a multiscale computational model of ATAA development in MFS mice as a reproducible, time- and cost-efficient complement to traditional animal experiments. The model implements a bidirectional coupling between a tissue-scale framework for aneurysm growth and remodeling and a cell-scale mechanobiological model for the ascending thoracic aorta. We calibrate and validate against experimental data from mouse studies capturing ATAA progression over time at both the tissue and cellular scales, either with or without pharmacological treatments. Following strong qualitative agreement with experimental observations, we employ the model for an in silico pharmacological treatment trial by simulating the inhibition or activation of various cell-scale model nodes. The simulations identify four novel medical treatments predicted to reduce the long-term failure risk of MFS-induced ATAAs, with inhibition of p38 mitogen-activated protein kinase emerging as the most promising option. Although simplified, the proposed model provides a robust, modular framework that can be readily extended or adapted in future research.
Insights
Marfan syndrome patients with aortic aneurysms may benefit from new computational models. These models predict novel treatments, including inhibiting p38 kinase, to reduce aneurysm failure risk.
Area of Science:
- Biomedical Engineering
- Computational Biology
- Genetics
Background:
- Marfan syndrome (MFS) is a genetic connective tissue disorder.
- Ascending thoracic aortic aneurysm (ATAA) is a life-threatening complication of MFS.
- Current treatments for MFS-induced ATAA are suboptimal due to incomplete understanding of cellular mechanisms.
Purpose of the Study:
- To develop a multiscale computational model of ATAA development in MFS mice.
- To use the model as a cost-efficient complement to animal studies.
- To identify novel therapeutic targets for MFS-induced ATAA.
Main Methods:
- A multiscale computational model coupling tissue-scale and cell-scale frameworks was developed.
- The model was calibrated and validated using experimental data from MFS mouse studies.
- In silico simulations were performed to test potential pharmacological interventions.
Main Results:
- The computational model demonstrated strong qualitative agreement with experimental observations.
- Simulations identified four novel potential treatments for MFS-induced ATAA.
- Inhibition of p38 mitogen-activated protein kinase was predicted as a highly promising therapeutic strategy.
Conclusions:
- The developed multiscale model offers a robust framework for studying ATAA in MFS.
- The model can guide the development of more effective treatments for MFS patients.
- Computational modeling provides a valuable tool for accelerating biomedical research and drug discovery.

