Komarova et al. (2003), Bone Remodeling
October 2007, model of the month by Anika Oellrich
Original model: BIOMD0000000148
Figure 1: Schematic representation of interactions between osteoclasts and osteoblasts included in the model. Thick arrows represent the processes of formation and removal of osteoclasts and osteoblasts. Fine arrows represent the effects of autocrine and paracrine regulators of bone remodeling on the rates of osteoclast and osteoblast formation. From .
Systems biology creates the tremendous opportunity to build models of processes happening inside the human body. These models can be used for analysing connections between disruptions in these processes and the origin of diseases. BIOMD0000000148  covers the processes of targeted and random bone remodeling [2,3] and a pathology similar to Paget's disease .
As shown in figure 1, the model contains two different types of cells: osteoclasts and osteoblasts. Following bone resorption caused by osteoclasts, resorbed bone tissue needs to be replaced with new bone material which is built by osteoblasts. The formation of both cell types is influenced by a large number of factors which are classified into autocrine and paracrine factors for each cell type [5,6]. One example for such an influencing factor is the transforming growth factor β (TGFβ).
TGFβ fulfills two tasks depending on the existence of osteoblasts: if they exist it inhibits osteoclastogenesis and if they are absent TGFβ activates osteoclast formation. The formation of osteoblasts is activated by insulin-like growth factor (IGF). Two important factors for the resorption of bone are Receptor activator of nuclear factor κB ligand (RANKL) and osteoprotegerin (OPG). RANKL stimulates osteoclast cells and therefore the removal of bone tissue. OPG reduces the interaction between RANKL and its receptor which reduces the destruction of bone.
The last and important part of the model is the bone mass, which is dependent on the resorption and formation of bone. Consequently, the mass of the bone is defined by the number of osteoclast and osteoblast cells in the model. This dependency can be seen in figure 2. With an increase in osteoclasts, the bone mass decreases, but this also stimulates the elevation of osteoblasts. The elevated number of osteoblasts promotes the formation of new bone tissue which starts after bone resorption.
Figure 2 also shows the stable oscillating behaviour of the model which occurs with a certain set of parameters and after stimulating the process once with an increase of osteoclasts out of the steady-state of both cell types.
Apart from one single bone remodeling cycle and the stable oscillation mode shown in figure 2, an unstable oscillation is possible. This unstable oscillation leads to an increase of the amplitude of bone mass which is similar to the pathological behavior of Paget's disease. Unstable oscillation within this model occurs when the effectiveness of osteoclast autocrine regulation increases or, out of a stable oscillation, when the effectiveness of osteoblast autocrine regulation rises.
Although the model is kept simple and small, it shows how relevant systems biology can be for analysing human body processes and discovering the origin of diseases.
Figure 2: Stable, intrinsically regulated oscillatory changes in bone cell numbers and bone mass, resembling random bone remodeling. (A) Changes with time in the number of osteoclasts (dashed line, axis on the left) and osteoblasts (solid line, axis on the right) following perturbation by a single increase in the number of osteoclasts by 10 cells at time 0. (B) Consequent changes in bone mass consist of a series of bone remodeling events, each resembling a single remodeling cycle. 100% represents the steady-state level of bone mass. From 
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