Mathematical modelling of bone remodelling cycles including the NFκB signalling pathway

Ji, Bing; Zhang, Yao; Zhen, Changqing; Fagan, Michael J.; Yang, Qing

Abstract

RANKL can promote the differentiation of osteoclast precursors into mature osteoclasts by binding to RANK expressed on the surfaces of osteoclast progenitor cells during bone remodelling. The NF-κB signalling pathway is downstream of RANKL and transmits the RANKL signal to nuclear promoter-bound protein complexes from cell surface receptors, which then regulates target gene expression to facilitate osteoclastogenesis. However, this important role of the NF-κB signalling pathway is usually ignored in published mathematical models of bone remodelling. This paper describes the construction of a mathematical model of bone remodelling in a normal bone microenvironment with inclusion of the NF-κB signalling pathway. The model consisted of a set of ordinary differential equations and reconstructed variations in the bone cells, resultant bone volume, and biochemical factors involved in the NF-κB signalling pathway over time. The model was used to investigate how the NF-κB pathway is activated in osteoclast precursors to promote osteoclastogenesis during bone remodelling. Model simulations agreed well with published experimental data. It is hoped that this model can improve our understanding of bone remodelling. It has the obvious potential to examine the influence of NF-κB dysregulation on bone remodelling, and even propose potential therapeutic strategies to combat related bone diseases in future research.

Citation

Ji, B., Zhang, Y., Zhen, C., Fagan, M. J., & Yang, Q. (2019). Mathematical modelling of bone remodelling cycles including the NFκB signalling pathway. Computers in biology and medicine, 107, 257-264. https://doi.org/10.1016/j.compbiomed.2019.03.003

• Journal Article Type: Article
• Acceptance Date: Mar 4, 2019
• Online Publication Date: Mar 8, 2019
• Publication Date: Apr 1, 2019
• Deposit Date: Mar 22, 2019
• Publicly Available Date: Mar 9, 2020
• Journal: Computers in Biology and Medicine
• Print ISSN: 0010-4825
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 107
• Pages: 257-264
• DOI: https://doi.org/10.1016/j.compbiomed.2019.03.003
• Keywords: Health Informatics; Computer Science Applications
• Public URL: https://hull-repository.worktribe.com/output/1381834
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0010482519300757?via%3Dihub
• Contract Date: Mar 22, 2019