Graham2013 - Role of osteocytes in targeted bone remodeling

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  • The role of osteocytes in targeted bone remodeling: a mathematical model.
  • Graham JM, Ayati BP, Holstein SA, Martin JA
  • PloS one , 1/ 2013 , Volume 8 , Issue 5 , pages: e63884 , PubMed ID: 23717504
  • Department of Mathematics, University of Scranton, Scranton, Pennsylvania, USA.
  • Until recently many studies of bone remodeling at the cellular level have focused on the behavior of mature osteoblasts and osteoclasts, and their respective precursor cells, with the role of osteocytes and bone lining cells left largely unexplored. This is particularly true with respect to the mathematical modeling of bone remodeling. However, there is increasing evidence that osteocytes play important roles in the cycle of targeted bone remodeling, in serving as a significant source of RANKL to support osteoclastogenesis, and in secreting the bone formation inhibitor sclerostin. Moreover, there is also increasing interest in sclerostin, an osteocyte-secreted bone formation inhibitor, and its role in regulating local response to changes in the bone microenvironment. Here we develop a cell population model of bone remodeling that includes the role of osteocytes, sclerostin, and allows for the possibility of RANKL expression by osteocyte cell populations. We have aimed to give a simple, yet still tractable, model that remains faithful to the underlying system based on the known literature. This model extends and complements many of the existing mathematical models for bone remodeling, but can be used to explore aspects of the process of bone remodeling that were previously beyond the scope of prior modeling work. Through numerical simulations we demonstrate that our model can be used to explore theoretically many of the qualitative features of the role of osteocytes in bone biology as presented in recent literature.
Submitter of the first revision: Sarubini Kananathan
Submitter of this revision: Sarubini Kananathan
Modellers: Sarubini Kananathan

Metadata information

is (2 statements)
BioModels Database MODEL1811150001
BioModels Database BIOMD0000000721

isDescribedBy (1 statement)
PubMed 23717504

hasTaxon (1 statement)
Taxonomy Homo sapiens

hasProperty (2 statements)
Mathematical Modelling Ontology Ordinary differential equation model
Gene Ontology bone remodeling

Curation status


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Model files

Model.xml SBML file of the model 47.16 KB Preview | Download

Additional files

V3 - ANNOTATED.cps Copasi file of the Model 84.48 KB Preview | Download

  • Model originally submitted by : Sarubini Kananathan
  • Submitted: Nov 15, 2018 1:48:10 PM
  • Last Modified: Nov 15, 2018 1:48:10 PM
  • Version: 4 public model Download this version
    • Submitted on: Nov 15, 2018 1:48:10 PM
    • Submitted by: Sarubini Kananathan
    • With comment: Automatically added model identifier BIOMD0000000721
: Variable used inside SBML models

Species Initial Concentration/Amount
Pre Osteoblasts P

0.0 mmol
Osteoblasts B

0.0 mmol
Bone volume z 100.0 mmol
Osteocytes S

180.0 mmol
Osteoclasts C

0.0 mmol
Reactions Rate Parameters
=> Pre_Osteoblasts__P; Osteocytes__S Bone*alpha_3*Pre_Osteoblasts__P^g_32*(1-Osteocytes__S/K_S) K_S = 200.0; g_32 = 1.0; alpha_3 = 0.1
Osteoblasts__B => Bone*beta_2*Osteoblasts__B^f_23 f_23 = 1.0; beta_2 = 0.1
Bone_volume__z => ; Osteoclasts__C Bone*k1*Osteoclasts__C k1 = 0.7
=> Bone_volume__z; Osteoblasts__B Bone*k2*Osteoblasts__B k2 = 0.015445
Osteoblasts__B => Osteocytes__S; Osteocytes__S Bone*alpha_1*Osteoblasts__B^g_31*(1-Osteocytes__S/K_S) g_31 = 1.0; alpha_1 = 0.5; K_S = 200.0
Pre_Osteoblasts__P => Bone*delta*Pre_Osteoblasts__P delta = 0.1
Pre_Osteoblasts__P => Osteoblasts__B; Osteoclasts__C Bone*beta_1*Pre_Osteoblasts__P^f_12*Osteoclasts__C^f_14 f_12 = 1.0; f_14 = 1.0; beta_1 = 0.1
Osteoclasts__C => Bone*beta_3*Osteoclasts__C^f_34 beta_3 = 0.1; f_34 = 1.0
Curator's comment:
(added: 15 Nov 2018, 13:47:43, updated: 15 Nov 2018, 13:47:43)
Figure 3 of the reference publication has been reproduced. Initial conditions and values were taken from the publication. Value for beta3 and rho was not stated in the paper, and through trial and error the values were estimated as 0.1 and 20 respectively. The model was simulated using Copasi 4.24 and the figure was generated using Python 3.7.