Mathematical modeling of signaling pathways in osteoarthritis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Purpose: Cartilage homeostasis relies on an intricate balance between anabolic and catabolic processes. In osteoarthritis this balance is shifted towards catabolism, leading to hypertrophy and a gradual degradation of cartilage tissue. So far, drug-based intervention in this process has shown limited progress. We propose to construct a mathematical model of the molecular network that governs key processes in articular cartilage homeostasis. This model can be used as a platform for model expansion by introduction of new experimental findings and hypotheses. Methods: We recently developed ANIMO (Analysis of Networks with Interactive Modeling), an intuitive software tool for modeling molecular networks. Here, we demonstrate a mathematical model of growth plate cartilage using a combination of literature and experimental data. We show how ANIMO allows for intuitive exploration of the model, despite the size and complexity of the model. Results: We constructed a network model of regulatory processes in growth plate chondrocytes. In this model the effects downstream of extracellular growth factors FGF, WNT, IGF-1, PTHrP, Ihh, BMP, and TGF-β are integrated into a cellular response. In silico experiments predict the phenotypic outcome for different inputs and starting states of the model. Osteoarthritic chondrocytes and hypertrophic growth plate chondrocytes show strong parallels in their gene expression profile. We have examined the gene expression profiles of growth plate and articular cartilage. In articular cartilage the expression of the WNT and BMP antagonists DKK1, FRZB and GREM1 is over 10-500 fold higher than in growth plate cartilage. This leads us to think that DKK1, FRZB, GREM1 could act as gatekeepers for preventing hypertrophy. We are currently investigating the range of conditions under which these proteins exert their stabilizing effect on the articular cartilage phenotype in the model. Furthermore, we are interrogating the model to obtain in silico leads to targets for novel combination therapies. Such therapies could be used to intervene in the osteoarthritic state of the network and restore the balanced situation of healthy cartilage. Conclusions: Traditionally, modeling efforts in the realm of molecular cell biology have been the exclusive domain of researchers with a thorough training in mathematics or computer science. We show here that a complex model that is intuitively amenable to exploration and adaptation by biologists is an invaluable asset in cartilage research. Expansion of an existing model with DKK1, FRZB and GREM1 provided evidence for their role in preserving the articular cartilage phenotype.
LanguageUndefined
Title of host publication2013 Osteoarthritis Research Society International (OARSI) World Congress
EditorsS. Lohmander
Place of PublicationAmsterdam
PublisherELSEVIER
Pages-
Number of pages1
DOIs
StatePublished - 19 Apr 2013
Event2013 OARSI World Congress on Osteoarthrtis - Philadelphia, United States
Duration: 18 Apr 201321 Apr 2013

Publication series

NameS123
PublisherOsteoArthritis Research Society International
No.Suppl.
Volume21
ISSN (Print)1063-4584
ISSN (Electronic)1522-9653

Conference

Conference2013 OARSI World Congress on Osteoarthrtis
CountryUnited States
CityPhiladelphia
Period18/04/1321/04/13

Keywords

  • dynamic modeling
  • Signaling pathways
  • EWI-23972
  • Osteoarthritis
  • IR-88364
  • METIS-300158
  • Timed Automata

Cite this

Scholma, J., Kerkhofs, J., Schivo, S., Langerak, R., van der Vet, P. E., Karperien, H. B. J., ... Post, J. N. (2013). Mathematical modeling of signaling pathways in osteoarthritis. In S. Lohmander (Ed.), 2013 Osteoarthritis Research Society International (OARSI) World Congress (pp. -). (S123; Vol. 21, No. Suppl.). Amsterdam: ELSEVIER. DOI: 10.1016/j.joca.2013.02.259
Scholma, Jetse ; Kerkhofs, J. ; Schivo, Stefano ; Langerak, Romanus ; van der Vet, P.E. ; Karperien, Hermanus Bernardus Johannes ; van de Pol, Jan Cornelis ; Geris, L. ; Post, Janine Nicole. / Mathematical modeling of signaling pathways in osteoarthritis. 2013 Osteoarthritis Research Society International (OARSI) World Congress. editor / S. Lohmander. Amsterdam : ELSEVIER, 2013. pp. - (S123; Suppl.).
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abstract = "Purpose: Cartilage homeostasis relies on an intricate balance between anabolic and catabolic processes. In osteoarthritis this balance is shifted towards catabolism, leading to hypertrophy and a gradual degradation of cartilage tissue. So far, drug-based intervention in this process has shown limited progress. We propose to construct a mathematical model of the molecular network that governs key processes in articular cartilage homeostasis. This model can be used as a platform for model expansion by introduction of new experimental findings and hypotheses. Methods: We recently developed ANIMO (Analysis of Networks with Interactive Modeling), an intuitive software tool for modeling molecular networks. Here, we demonstrate a mathematical model of growth plate cartilage using a combination of literature and experimental data. We show how ANIMO allows for intuitive exploration of the model, despite the size and complexity of the model. Results: We constructed a network model of regulatory processes in growth plate chondrocytes. In this model the effects downstream of extracellular growth factors FGF, WNT, IGF-1, PTHrP, Ihh, BMP, and TGF-β are integrated into a cellular response. In silico experiments predict the phenotypic outcome for different inputs and starting states of the model. Osteoarthritic chondrocytes and hypertrophic growth plate chondrocytes show strong parallels in their gene expression profile. We have examined the gene expression profiles of growth plate and articular cartilage. In articular cartilage the expression of the WNT and BMP antagonists DKK1, FRZB and GREM1 is over 10-500 fold higher than in growth plate cartilage. This leads us to think that DKK1, FRZB, GREM1 could act as gatekeepers for preventing hypertrophy. We are currently investigating the range of conditions under which these proteins exert their stabilizing effect on the articular cartilage phenotype in the model. Furthermore, we are interrogating the model to obtain in silico leads to targets for novel combination therapies. Such therapies could be used to intervene in the osteoarthritic state of the network and restore the balanced situation of healthy cartilage. Conclusions: Traditionally, modeling efforts in the realm of molecular cell biology have been the exclusive domain of researchers with a thorough training in mathematics or computer science. We show here that a complex model that is intuitively amenable to exploration and adaptation by biologists is an invaluable asset in cartilage research. Expansion of an existing model with DKK1, FRZB and GREM1 provided evidence for their role in preserving the articular cartilage phenotype.",
keywords = "dynamic modeling, Signaling pathways, EWI-23972, Osteoarthritis, IR-88364, METIS-300158, Timed Automata",
author = "Jetse Scholma and J. Kerkhofs and Stefano Schivo and Romanus Langerak and {van der Vet}, P.E. and Karperien, {Hermanus Bernardus Johannes} and {van de Pol}, {Jan Cornelis} and L. Geris and Post, {Janine Nicole}",
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Scholma, J, Kerkhofs, J, Schivo, S, Langerak, R, van der Vet, PE, Karperien, HBJ, van de Pol, JC, Geris, L & Post, JN 2013, Mathematical modeling of signaling pathways in osteoarthritis. in S Lohmander (ed.), 2013 Osteoarthritis Research Society International (OARSI) World Congress. S123, no. Suppl., vol. 21, ELSEVIER, Amsterdam, pp. -, 2013 OARSI World Congress on Osteoarthrtis, Philadelphia, United States, 18/04/13. DOI: 10.1016/j.joca.2013.02.259

Mathematical modeling of signaling pathways in osteoarthritis. / Scholma, Jetse; Kerkhofs, J.; Schivo, Stefano; Langerak, Romanus; van der Vet, P.E.; Karperien, Hermanus Bernardus Johannes; van de Pol, Jan Cornelis; Geris, L.; Post, Janine Nicole.

2013 Osteoarthritis Research Society International (OARSI) World Congress. ed. / S. Lohmander. Amsterdam : ELSEVIER, 2013. p. - (S123; Vol. 21, No. Suppl.).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Mathematical modeling of signaling pathways in osteoarthritis

AU - Scholma,Jetse

AU - Kerkhofs,J.

AU - Schivo,Stefano

AU - Langerak,Romanus

AU - van der Vet,P.E.

AU - Karperien,Hermanus Bernardus Johannes

AU - van de Pol,Jan Cornelis

AU - Geris,L.

AU - Post,Janine Nicole

N1 - 2013 Osteoarthritis Research Society International (OARSI)World Congress being held in Philadelphia, Pennsylvania from April 18–21, 2013

PY - 2013/4/19

Y1 - 2013/4/19

N2 - Purpose: Cartilage homeostasis relies on an intricate balance between anabolic and catabolic processes. In osteoarthritis this balance is shifted towards catabolism, leading to hypertrophy and a gradual degradation of cartilage tissue. So far, drug-based intervention in this process has shown limited progress. We propose to construct a mathematical model of the molecular network that governs key processes in articular cartilage homeostasis. This model can be used as a platform for model expansion by introduction of new experimental findings and hypotheses. Methods: We recently developed ANIMO (Analysis of Networks with Interactive Modeling), an intuitive software tool for modeling molecular networks. Here, we demonstrate a mathematical model of growth plate cartilage using a combination of literature and experimental data. We show how ANIMO allows for intuitive exploration of the model, despite the size and complexity of the model. Results: We constructed a network model of regulatory processes in growth plate chondrocytes. In this model the effects downstream of extracellular growth factors FGF, WNT, IGF-1, PTHrP, Ihh, BMP, and TGF-β are integrated into a cellular response. In silico experiments predict the phenotypic outcome for different inputs and starting states of the model. Osteoarthritic chondrocytes and hypertrophic growth plate chondrocytes show strong parallels in their gene expression profile. We have examined the gene expression profiles of growth plate and articular cartilage. In articular cartilage the expression of the WNT and BMP antagonists DKK1, FRZB and GREM1 is over 10-500 fold higher than in growth plate cartilage. This leads us to think that DKK1, FRZB, GREM1 could act as gatekeepers for preventing hypertrophy. We are currently investigating the range of conditions under which these proteins exert their stabilizing effect on the articular cartilage phenotype in the model. Furthermore, we are interrogating the model to obtain in silico leads to targets for novel combination therapies. Such therapies could be used to intervene in the osteoarthritic state of the network and restore the balanced situation of healthy cartilage. Conclusions: Traditionally, modeling efforts in the realm of molecular cell biology have been the exclusive domain of researchers with a thorough training in mathematics or computer science. We show here that a complex model that is intuitively amenable to exploration and adaptation by biologists is an invaluable asset in cartilage research. Expansion of an existing model with DKK1, FRZB and GREM1 provided evidence for their role in preserving the articular cartilage phenotype.

AB - Purpose: Cartilage homeostasis relies on an intricate balance between anabolic and catabolic processes. In osteoarthritis this balance is shifted towards catabolism, leading to hypertrophy and a gradual degradation of cartilage tissue. So far, drug-based intervention in this process has shown limited progress. We propose to construct a mathematical model of the molecular network that governs key processes in articular cartilage homeostasis. This model can be used as a platform for model expansion by introduction of new experimental findings and hypotheses. Methods: We recently developed ANIMO (Analysis of Networks with Interactive Modeling), an intuitive software tool for modeling molecular networks. Here, we demonstrate a mathematical model of growth plate cartilage using a combination of literature and experimental data. We show how ANIMO allows for intuitive exploration of the model, despite the size and complexity of the model. Results: We constructed a network model of regulatory processes in growth plate chondrocytes. In this model the effects downstream of extracellular growth factors FGF, WNT, IGF-1, PTHrP, Ihh, BMP, and TGF-β are integrated into a cellular response. In silico experiments predict the phenotypic outcome for different inputs and starting states of the model. Osteoarthritic chondrocytes and hypertrophic growth plate chondrocytes show strong parallels in their gene expression profile. We have examined the gene expression profiles of growth plate and articular cartilage. In articular cartilage the expression of the WNT and BMP antagonists DKK1, FRZB and GREM1 is over 10-500 fold higher than in growth plate cartilage. This leads us to think that DKK1, FRZB, GREM1 could act as gatekeepers for preventing hypertrophy. We are currently investigating the range of conditions under which these proteins exert their stabilizing effect on the articular cartilage phenotype in the model. Furthermore, we are interrogating the model to obtain in silico leads to targets for novel combination therapies. Such therapies could be used to intervene in the osteoarthritic state of the network and restore the balanced situation of healthy cartilage. Conclusions: Traditionally, modeling efforts in the realm of molecular cell biology have been the exclusive domain of researchers with a thorough training in mathematics or computer science. We show here that a complex model that is intuitively amenable to exploration and adaptation by biologists is an invaluable asset in cartilage research. Expansion of an existing model with DKK1, FRZB and GREM1 provided evidence for their role in preserving the articular cartilage phenotype.

KW - dynamic modeling

KW - Signaling pathways

KW - EWI-23972

KW - Osteoarthritis

KW - IR-88364

KW - METIS-300158

KW - Timed Automata

U2 - 10.1016/j.joca.2013.02.259

DO - 10.1016/j.joca.2013.02.259

M3 - Conference contribution

T3 - S123

SP - -

BT - 2013 Osteoarthritis Research Society International (OARSI) World Congress

PB - ELSEVIER

CY - Amsterdam

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Scholma J, Kerkhofs J, Schivo S, Langerak R, van der Vet PE, Karperien HBJ et al. Mathematical modeling of signaling pathways in osteoarthritis. In Lohmander S, editor, 2013 Osteoarthritis Research Society International (OARSI) World Congress. Amsterdam: ELSEVIER. 2013. p. -. (S123; Suppl.). Available from, DOI: 10.1016/j.joca.2013.02.259