Dataset Information

Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis - Age Dependent

ABSTRACT: Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis - Age Dependant This model by Baker M. 2013, describes the interaction between pro and anti-inflammatory cytokine signalling in rheumatoid arthritis. Using two ordinary differential equations, the first model [BIOMD0000000550] analyses bifurcation and describes different pathological states by altering inflammatory regulation parameters. The second model [BIOMD0000000549] includes the effect that ageing has on pro-inflammatory signalling, allowing for time-dependant properties and disease progression to be observed. The author also describes potential dosing for reversal of the disease state. This model is described in the article: Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis. Baker M, Denman-Johnson S, Brook BS, Gaywood I, Owen MR. Math Med Biol 2013 Dec; 30(4): 311-337 Abstract: Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interactions. This paper considers a two-variable model for the interactions between pro-inflammatory and anti-inflammatory cytokines, and demonstrates that mathematical modelling may be used to investigate the involvement of cytokines in the disease process. The model displays a range of possible behaviours, such as bistability and oscillations, which are strongly reminiscent of the behaviour of RA e.g. genetic susceptibility and remitting-relapsing disease. We also show that the dose regimen as well as the dose level are important factors in RA treatments. This model is hosted on BioModels Database and identified by: BIOMD0000000549. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

DISEASE(S): Rheumatoid Arthritis

SUBMITTER: Vincent Knight-Schrijver

PROVIDER: BIOMD0000000549 | BioModels | 2024-09-02

REPOSITORIES: BioModels

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	BIOMD0000000549?filename=BIOMD0000000549-biopax2.owl	Owl
	BIOMD0000000549?filename=BIOMD0000000549-biopax3.owl	Owl
	BIOMD0000000549?filename=BIOMD0000000549-matlab.m	Other
	BIOMD0000000549?filename=BIOMD0000000549-octave.m	Other
	BIOMD0000000549?filename=BIOMD0000000549.m	Other

Items per page:

1 - 5 of 15

Publications

Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis.

Baker Michelle M Denman-Johnson Sarah S Brook Bindi S BS Gaywood Ian I Owen Markus R MR

Mathematical medicine and biology : a journal of the IMA 20120920 4

Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interacti ...[more]

PMID: 23002057

Similar Datasets

Project description:Baker2013 - Cytokine Mediated Inflammation in Rheumatoid Arthritis This model by Baker M. 2013, describes the interaction between pro and anti-inflammatory cytokine signalling in rheumatoid arthritis. Using two ordinary differential equations, the first model [BIOMD0000000550] analyses bifurcation and describes different pathological states by altering inflammatory regulation parameters. The second model [BIOMD0000000549] includes the effect that ageing has on pro-inflammatory signalling, allowing for time-dependant properties and disease progression to be observed. The author also describes potential dosing for reversal of the disease state. This model is described in the article: Mathematical modelling of cytokine-mediated inflammation in rheumatoid arthritis. Baker M, Denman-Johnson S, Brook BS, Gaywood I, Owen MR. Math Med Biol 2013 Dec; 30(4): 311-337 Abstract: Rheumatoid arthritis (RA) is a chronic inflammatory disease preferentially affecting the joints and leading, if untreated, to progressive joint damage and disability. Cytokines, a group of small inducible proteins, which act as intercellular messengers, are key regulators of the inflammation that characterizes RA. They can be classified into pro-inflammatory and anti-inflammatory groups. Numerous cytokines have been implicated in the regulation of RA with complex up and down regulatory interactions. This paper considers a two-variable model for the interactions between pro-inflammatory and anti-inflammatory cytokines, and demonstrates that mathematical modelling may be used to investigate the involvement of cytokines in the disease process. The model displays a range of possible behaviours, such as bistability and oscillations, which are strongly reminiscent of the behaviour of RA e.g. genetic susceptibility and remitting-relapsing disease. We also show that the dose regimen as well as the dose level are important factors in RA treatments. This model is hosted on BioModels Database and identified by: BIOMD0000000550. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Baker2017 - The role of cytokines, MMPs and fibronectin fragments osteoarthritis This model is described in the article: Mathematical modelling of cytokines, MMPs and fibronectin fragments in osteoarthritic cartilage. Baker M, Brook BS, Owen MR. J Math Biol 2017 Feb; : Abstract: Osteoarthritis (OA) is a degenerative disease which causes pain and stiffness in joints. OA progresses through excessive degradation of joint cartilage, eventually leading to significant joint degeneration and loss of function. Cytokines, a group of cell signalling proteins, present in raised concentrations in OA joints, can be classified into pro-inflammatory and anti-inflammatory groups. They mediate cartilage degradation through several mechanisms, primarily the up-regulation of matrix metalloproteinases (MMPs), a group of collagen-degrading enzymes. In this paper we show that the interactions of cytokines within cartilage have a crucial role to play in OA progression and treatment. We develop a four-variable ordinary differential equation model for the interactions between pro- and anti-inflammatory cytokines, MMPs and fibronectin fragments (Fn-fs), a by-product of cartilage degradation and up-regulator of cytokines. We show that the model has four classes of dynamic behaviour: homoeostasis, bistable inflammation, tristable inflammation and persistent inflammation. We show that positive and negative feedbacks controlling cytokine production rates can determine either a pre-disposition to OA or initiation of OA. Further, we show that manipulation of cytokine, MMP and Fn-fs levels can be used to treat OA, but we suggest that multiple treatment targets may be essential to halt or slow disease progression. This model is hosted on BioModels Database and identified by: MODEL1704120000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Background. Rheumatoid arthritis (RA) is a chronic inflammatory and destructive joint disease, characterized by overexpression of pro-inflammatory/-destructive genes and other activating genes (e.g., proto-oncogenes) in the synovial membrane (SM). The gene expression in disease is often characterized by significant inter-individual variances via specific synchronization/ desynchronization of gene expression. To elucidate the contribution of the variance to the pathogenesis of disease, expression variances were tested in SM samples of RA patients, osteoarthritis (OA) patients, and normal controls (NC). Results. For the comparison between RA and NC, 568 genes with significantly different variances in the 2 groups (p < 0.05; Bonferroni/Holm corrected Brown-Forsythe version of the Levene-Test) were selected. For the comparison between RA and OA, 333 genes were selected. Using the Kyoto encyclopedia of genes and genomes (KEGG), 10 pathways/complexes significantly affected by higher gene expression variances were identified in RA compared to NC, including cytokine â cytokine receptor interactions, the TGF-pathway, and anti-apoptosis. Compared to OA, 3 pathways with significantly higher variances were identified in RA (e.g., B cell receptor signaling, VEGF signaling). Functionally, the majority of the identified pathways is involved in the regulation of inflammation, proliferation, cell survival, and angiogenesis. Conclusion. In RA, a number of disease-relevant or even disease-specific pathways/complexes are characterized by broad intra-group, inter-individual expression variances. This indicates that RA pathogenesis in different individuals may depend to a lesser extent on common alterations of the expression of specific key genes, but on individual-specific alterations of different genes resulting in common disturbances of key pathways. Experiment Overall Design: Expression variances were tested in synovial membrane samples of rheumatoid arthritis patients, osteoarthritis patients, and normal controls (see publication for further details).

Project description:The pathogenesis of rheumatoid arthritis (RA) is complicated and involves both innate and adaptive immunity [5]. The innate immunity such as macrophages or fibroblast-like synoviocytes (FLS) in the synovium can generate inflammatory mediators, including TNF-α, IL-1, IL-6, IL-17, IFN-γ, and chemo kines that lead to synovial inflammation, bone erosion, and cartilage damage [6-8]. The IL-17 signaling mediates the autoantibody production in collagen-induced arthritis (CIA) model [9]. However, the treatment response with an anti-IL17 monoclonal antibody in RA patients shows a high degree of heterogeneity [10]. The inhibitors of the Janus kinase (JAK) pathway are approved for RA patients [11]. These data suggest that the targeted multiple cytokines through the JAK pathway are useful for RA treatment. Disturbance of type I IFNs (IFNs-I) signaling and production drive autoimmune development [12]. The presymptomatic RA patients display an increase of IFNs-I before the onset of symptoms [13]. The RA patients also show the elevation of IFN- α in the synovial fluid and high expression of IFNs-I regulated gene in peripheral blood mononuclear cells (PBMC) [14]. However, the role of IFNs-I in arthritis and bone homeostasis has suggested the accelerating effect of arthritis and bone damage. The interferon-alpha receptor knockout mice develop arthritis severity higher than wild-type mice in the model of antigen-induced arthritis [15]. IFNs-I also affects the bone homeostasis by inhibiting osteoclastogenesis via receptor activator of nuclear factor-kappa B (RANK) pathway, and reduction of c-FOS expression [16-18]. Therefore, the goal of RA treatment with antagonizing the IFNs-I pathway has to be optimized between efficacy and potentially adverse effect. STING is a cytosolic DNA sensor that initiates the production of IFNs-I. STING functions have been reported as both pro-inflammatory signaling and negative regulator against inflammation [19-21]. The mutation in exon 5 of the STING gene results in gain function leading to initiate inflammation and cause the Sting associated vasculopathy with onset in infancy (SAVI) [22]. Loss of STING function rescues DNaseII-deficient mice from lethality and polyarthritis [23]. However, Sting-deficient lupus mice (MRL/Lpr mice) show higher and earlier mortality than Sting-sufficient MRL/Lpr mice [24]. The pathology also shows lymphoid hypertrophy with a higher amount of macrophages and granulocytes infiltration, autoantibodies, and cytokine [24]. The objective of this study was to identify the role of STING in the pathogenesis of rheumatoid arthritis using collagen-induced arthritis (CIA) model as a representative model of the human RA.

Project description:Rheumatoid arthritis is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-?, IL-6, IL-12p70, and IFN-?. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis. A total of 556 human sera were profiled using multiplex cytokine and chemokine assays. The cohort was comprised of 80 patients with clinical RA for whom stored serum was available from 1-10 years prior to disease onset and 78 control subjects without RA matched to cases based on age, gender, race, region of assignment, and time of serum sampling.

Project description:Dunster2014 - WBC Interactions (Model1) This is a sub-model of a three-step inflammatory response modelling study. The model includes distinct populations of white blood cells namely, macrophages and active and apoptotic neutrophil populations. Neutrophil apoptosis rate is predicted to be crucial for the qualitative nature of the system. This model is described in the article: The resolution of inflammation: a mathematical model of neutrophil and macrophage interactions. Dunster JL, Byrne HM, King JR. Bull. Math. Biol. 2014 Aug; 76(8): 1953-1980 Abstract: There is growing interest in inflammation due to its involvement in many diverse medical conditions, including Alzheimer's disease, cancer, arthritis and asthma. The traditional view that resolution of inflammation is a passive process is now being superceded by an alternative hypothesis whereby its resolution is an active, anti-inflammatory process that can be manipulated therapeutically. This shift in mindset has stimulated a resurgence of interest in the biological mechanisms by which inflammation resolves. The anti-inflammatory processes central to the resolution of inflammation revolve around macrophages and are closely related to pro-inflammatory processes mediated by neutrophils and their ability to damage healthy tissue. We develop a spatially averaged model of inflammation centring on its resolution, accounting for populations of neutrophils and macrophages and incorporating both pro- and anti-inflammatory processes. Our ordinary differential equation model exhibits two outcomes that we relate to healthy and unhealthy states. We use bifurcation analysis to investigate how variation in the system parameters affects its outcome. We find that therapeutic manipulation of the rate of macrophage phagocytosis can aid in resolving inflammation but success is critically dependent on the rate of neutrophil apoptosis. Indeed our model predicts that an effective treatment protocol would take a dual approach, targeting macrophage phagocytosis alongside neutrophil apoptosis. This model is hosted on BioModels Database and identified by: BIOMD0000000616. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:Rheumatoid arthritis is a prototypical autoimmune arthritis affecting nearly 1% of the world population and is a significant cause of worldwide disability. Though prior studies have demonstrated the appearance of RA-related autoantibodies years before the onset of clinical RA, the pattern of immunologic events preceding the development of RA remains unclear. To characterize the evolution of the autoantibody response in the preclinical phase of RA, we used a novel multiplex autoantigen array to evaluate development of the anti-citrullinated protein antibodies (ACPA) and to determine if epitope spread correlates with rise in serum cytokines and imminent onset of clinical RA. To do so, we utilized a cohort of 81 patients with clinical RA for whom stored serum was available from 1-12 years prior to disease onset. We evaluated the accumulation of ACPA subtypes over time and correlated this accumulation with elevations in serum cytokines. We then used logistic regression to identify a profile of biomarkers which predicts the imminent onset of clinical RA (defined as within 2 years of testing). We observed a time-dependent expansion of ACPA specificity with the number of ACPA subtypes. At the earliest timepoints, we found autoantibodies targeting several innate immune ligands including citrullinated histones, fibrinogen, and biglycan, thus providing insights into the earliest autoantigen targets and potential mechanisms underlying the onset and development of autoimmunity in RA. Additionally, expansion of the ACPA response strongly predicted elevations in many inflammatory cytokines including TNF-α, IL-6, IL-12p70, and IFN-γ. Thus, we observe that the preclinical phase of RA is characterized by an accumulation of multiple autoantibody specificities reflecting the process of epitope spread. Epitope expansion is closely correlated with the appearance of preclinical inflammation, and we identify a biomarker profile including autoantibodies and cytokines which predicts the imminent onset of clinical arthritis. A total of 559 human sera were profiled using a custom made panel of putative rheumatoid arthritis associated autoantigens. The cohort was comprised of 79 patients with clinical RA for whom stored serum was available from 1-10 years prior to disease onset and 80 control subjects without RA that were matched to cases based on age, gender, race, region of assignment, and time of serum sampling.