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.

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.