Proctor2017- Role of microRNAs in osteoarthritis (miR140-SMAD3 double negative feedback)

Proctor2017- Role of microRNAs in
osteoarthritis (miR140-SMAD3 double negative feedback)

This model is described in the article:

Computer simulation models
as a tool to investigate the role of microRNAs in
osteoarthritis.

Proctor CJ, Smith GR.
PLoS ONE 2017; 12(11): e0187568
Abstract:

The aim of this study was to show how computational models
can be used to increase our understanding of the role of
microRNAs in osteoarthritis (OA) using miR-140 as an example.
Bioinformatics analysis and experimental results from the
literature were used to create and calibrate models of gene
regulatory networks in OA involving miR-140 along with key
regulators such as NF-?B, SMAD3, and RUNX2. The individual
models were created with the modelling standard, Systems
Biology Markup Language, and integrated to examine the overall
effect of miR-140 on cartilage homeostasis. Down-regulation of
miR-140 may have either detrimental or protective effects for
cartilage, indicating that the role of miR-140 is complex.
Studies of individual networks in isolation may therefore lead
to different conclusions. This indicated the need to combine
the five chosen individual networks involving miR-140 into an
integrated model. This model suggests that the overall effect
of miR-140 is to change the response to an IL-1 stimulus from a
prolonged increase in matrix degrading enzymes to a pulse-like
response so that cartilage degradation is temporary. Our
current model can easily be modified and extended as more
experimental data become available about the role of miR-140 in
OA. In addition, networks of other microRNAs that are important
in OA could be incorporated. A fully integrated model could not
only aid our understanding of the mechanisms of microRNAs in
ageing cartilage but could also provide a useful tool to
investigate the effect of potential interventions to prevent
cartilage loss.

This model is hosted on
BioModels Database
and identified by:
MODEL1705170000.
To cite BioModels Database, please use:
Chelliah V et al. BioModels: ten-year
anniversary. Nucl. Acids Res. 2015, 43(Database
issue):D542-8.

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