Higher-order adaptive dynamical system modeling of the role of epigenetics in Rett Syndrome
Tinmiouli,Marwa Hendrikse,Sophie C. F. Treur,Jan
Tinmiouli,Marwa
Hendrikse,Sophie C. F.
Treur,Jan
Abstract
This paper introduces a higher-order adaptive self-modelling network model to simulate the role of epigenetics in the development and treatment of Rett syndrome (RTT). RTT is a neurodevelopmental disorder caused by mutations in the MECP2 gene. The model is constructed using temporal-causal network modeling principles and integrates multiple levels of biological and emotional adaptation. While MECP2 dysfunction is central to RTT, recent findings emphasize the role of environmental factors, mainly early-life stress. One of the epigenetic consequences of this stress, is the reduced expression of brain-derived neurotrophic factor (BDNF) and widespread dysfunction in emotional and cognitive regulation. In this study, a computational simulation is used to explore both the development of RTT and the potential effectiveness of a hypothetical epigenetic therapy aimed at restoring BDNF expression. The results highlight how targeted intervention could reverse or mitigate the long-term neurological impacts of RTT.
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Date
2025
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Springer Nature
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Tinmiouli, M, Hendrikse, S C F & Treur, J 2025, Higher-order adaptive dynamical system modeling of the role of epigenetics in Rett Syndrome. in Proc. of the 9th computational methods in systems and software conference. Lecture Notes in Networks and Systems, Springer Nature, the 9th Computational methods in systems and software conference, 29/10/25. < https://www.researchgate.net/publication/395482598 >
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info:eu-repo/semantics/restrictedAccess