ABSTRACT NUMBER: ESOC2026YS234 MATHEMATICAL MODELLING OF GENOTYPE-DEPENDENT TGF-Β SIGNALLING IN INTRACRANIAL ANEURYSM PROGRESSION

Abstract Background and aims Patient-specific genetic analysis has the potential to personalise and improve the prediction of intracranial aneurysm evolution, risk of rupture and treatment response [1]. We integrate for the first time genetic data into a mathematical model of aneurysm evolution and treatment for the purpose of testing the effect of genetic variability on aneurysm growth and response to pharmacological treatment. Methods We extend a mathematical model of arterial wall mechanobiology that includes wall constituents (elastin, vascular smooth muscle cells (VSMCs), collagen, etc.) with their mechanical properties and the molecular signalling network that regulates their biological function [2]. The model predicts aneurysm growth following elastin degradation and simulates treatment via pulse administration of TGF-β1 to promote collagen synthesis and stabilise the wall. The extension adds distinct parametrisations according to the genotypic expression of genetic variant rs1800470, which regulates expression of TGF-β1 in blood, and explores outcome variability in aneurysm diameter, response to treatment, cell and protein densities as well as molecular signalling regulation. Results Analysis is complete for genetic variant rs1800470: as expected, more sensitive genotypes result in slower growth and higher sensitivity to treatment, although the effect size is small due to the consideration of a single gene. Work is ongoing to integrate a second TGF-β1-related gene and to include the mechanobiology of VSMCs, differentially parametrised according to a related polygenic score. 1. Bakker et al., Nature Genetics, https://doi.org/10.1038/s41588-020-00725-7. 2. Aparício et al., J. Biomech., https://doi.org/10.1016/j.jbiomech.2016.04.037 Conflict of interest Zainab Nasser: nothing to disclose. Mark Bakker: nothing to disclose. Giulia Pederzani: nothing to disclose.