Komarova Svetlana V, Safranek Lee, Gopalakrishnan Jay, Ou Miao-Jung Yvonne, McKee Marc D, Murshed Monzur, Rauch Frank, Zuhr Erica
Faculty of Dentistry, McGill University Montreal, QC, Canada ; Shriners Hospital for Children-Canada Montreal, QC, Canada.
Department of Mathematics, Simon Fraser University Burnaby, BC, Canada.
Front Cell Dev Biol. 2015 Aug 21;3:51. doi: 10.3389/fcell.2015.00051. eCollection 2015.
Defective bone mineralization has serious clinical manifestations, including deformities and fractures, but the regulation of this extracellular process is not fully understood. We have developed a mathematical model consisting of ordinary differential equations that describe collagen maturation, production and degradation of inhibitors, and mineral nucleation and growth. We examined the roles of individual processes in generating normal and abnormal mineralization patterns characterized using two outcome measures: mineralization lag time and degree of mineralization. Model parameters describing the formation of hydroxyapatite mineral on the nucleating centers most potently affected the degree of mineralization, while the parameters describing inhibitor homeostasis most effectively changed the mineralization lag time. Of interest, a parameter describing the rate of matrix maturation emerged as being capable of counter-intuitively increasing both the mineralization lag time and the degree of mineralization. We validated the accuracy of model predictions using known diseases of bone mineralization such as osteogenesis imperfecta and X-linked hypophosphatemia. The model successfully describes the highly nonlinear mineralization dynamics, which includes an initial lag phase when osteoid is present but no mineralization is evident, then fast primary mineralization, followed by secondary mineralization characterized by a continuous slow increase in bone mineral content. The developed model can potentially predict the function for a mutated protein based on the histology of pathologic bone samples from mineralization disorders of unknown etiology.
骨矿化缺陷具有严重的临床表现,包括畸形和骨折,但这种细胞外过程的调控机制尚未完全明确。我们构建了一个由常微分方程组成的数学模型,该模型描述了胶原蛋白成熟、抑制剂的产生和降解,以及矿物质成核和生长过程。我们使用矿化延迟时间和矿化程度这两个结果指标,研究了各个过程在产生正常和异常矿化模式中的作用。描述羟基磷灰石矿物质在成核中心形成的模型参数对矿化程度影响最为显著,而描述抑制剂稳态的参数则最有效地改变了矿化延迟时间。有趣的是,一个描述基质成熟速率的参数竟然能够反常地同时增加矿化延迟时间和矿化程度。我们使用诸如成骨不全症和X连锁低磷血症等已知的骨矿化疾病验证了模型预测的准确性。该模型成功地描述了高度非线性的矿化动力学,包括当类骨质存在但无明显矿化时的初始延迟阶段,然后是快速的初级矿化,接着是次级矿化,其特征是骨矿物质含量持续缓慢增加。所开发的模型有可能根据病因不明的矿化障碍的病理骨样本组织学来预测突变蛋白的功能。