A multiscale computational model of ascending thoracic aortic aneurysm development in Marfan syndrome for in silico trials.

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.