Osteoporosis is a bone disease characterized by brittle bone and increased fracture incidence. With ageing societies worldwide, the disease presents a high burden on health systems. Furthermore, there are limited treatments for osteoporosis with just two anabolic pharmacological agents approved by the US Food and Drug Administration. Healthy bones are believed to be maintained via an intricate relationship between dual biochemical and mechanical (bio-mechanical) stimulations. It is widely considered that osteoporosis emerges as a result of disturbances to said relationship. The mechanotransduction process is key to this balance, and disruption of its dynamics in bone cells plays a role in osteoporosis development. Nonetheless, the exact details and mechanisms that drive and secure the health of bones are still elusive at the cellular and molecular scales. This study examined the dual modulation of mechanical stimulation and mechanotransduction activation dynamics in an osteoblast (OB). The aim was to find patterns of mechanotransduction dynamics demonstrating a significant change that can be mapped to alterations in the OB responses, specifically at the level of gene expression and osteogenic markers such as alkaline phosphatase. This was achieved using a three-dimensional hybrid multiscale computational model simulating mechanotransduction in the OB and its interaction with the extracellular matrix, combined with a numerical analytical technique. The model and the analysis method predict that within the noise of mechanotransduction, owing to modulation of the bio-mechanical stimulus and consequent gene expression, there are unique events that provide signatures for a shift in the system's dynamics. Furthermore, the study uncovered molecular interactions that can be potential drug targets.
CITATION STYLE
Ascolani, G., Skerry, T. M., Lacroix, D., Dall’Ara, E., & Shuaib, A. (2021). Analysis of mechanotransduction dynamics during combined mechanical stimulation and modulation of the extracellular-regulated kinase cascade uncovers hidden information within the signalling noise: Computational Biomedicine. Interface Focus, 11(1). https://doi.org/10.1098/rsfs.2019.0136
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