Computer Laboratory, Cambridge University, William Gates Building, 15 JJ Thomson Avenue, Cambridge CB3 0FD, UK.
BMC Bioinformatics. 2012;13 Suppl 14(Suppl 14):S12. doi: 10.1186/1471-2105-13-S14-S12. Epub 2012 Sep 7.
This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. The infection rapidly leads to severe bone loss, necrosis of the affected portion, and it may even spread to other parts of the body. On the other hand, osteoporosis is not a bacterial infection but similarly is a defective bone pathology arising due to imbalances in the RANK/RANKL/OPG molecular pathway, and due to the progressive weakening of bone structure.
Since both osteoporosis and osteomyelitis cause loss of bone mass, we focused on comparing the dynamics of these diseases by means of computational models. Firstly, we performed meta-analysis on a gene expression data of normal, osteoporotic and osteomyelitis bone conditions. We mainly focused on RANKL/OPG signalling, the TNF and TNF receptor superfamilies and the NF-kB pathway. Using information from the gene expression data we estimated parameters for a novel model of osteoporosis and of osteomyelitis. Our models could be seen as a hybrid ODE and probabilistic verification modelling framework which aims at investigating the dynamics of the effects of the infection in bone remodelling. Finally we discuss different diagnostic estimators defined by formal verification techniques, in order to assess different bone pathologies (osteopenia, osteoporosis and osteomyelitis) in an effective way.
We present a modeling framework able to reproduce aspects of the different bone remodeling defective dynamics of osteomyelitis and osteoporosis. We report that the verification-based estimators are meaningful in the light of a feed forward between computational medicine and clinical bioinformatics.
本工作专注于骨髓炎的计算建模，骨髓炎是一种由细菌感染（主要是金黄色葡萄球菌）引起的骨病理学。感染改变了 RANK/RANKL/OPG 信号通路，该通路调节了成骨细胞和破骨细胞在骨重塑中的行为，即吸收和矿化活性。感染迅速导致严重的骨质流失、受影响部位的坏死，甚至可能扩散到身体的其他部位。另一方面，骨质疏松症不是细菌感染，但同样是一种由于 RANK/RANKL/OPG 分子通路失衡以及骨骼结构逐渐减弱而导致的有缺陷的骨病理学。
由于骨质疏松症和骨髓炎都会导致骨量丢失，我们专注于通过计算模型比较这些疾病的动态。首先，我们对正常、骨质疏松症和骨髓炎骨条件的基因表达数据进行了荟萃分析。我们主要关注 RANKL/OPG 信号通路、TNF 和 TNF 受体超家族以及 NF-kB 通路。利用基因表达数据中的信息，我们为骨质疏松症和骨髓炎的新型模型估计了参数。我们的模型可以被视为一种混合的 ODE 和概率验证建模框架，旨在研究感染对骨重塑动态的影响。最后，我们讨论了形式验证技术定义的不同诊断估计器，以便有效地评估不同的骨病理学（低骨量、骨质疏松症和骨髓炎）。
我们提出了一个建模框架，能够再现骨髓炎和骨质疏松症不同骨重塑缺陷动态的某些方面。我们报告说，基于验证的估计器在计算医学和临床生物信息学之间的前馈中有意义。
