BMC Bioinformatics - This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the...
Biology of the RANKL–RANK–OPG System in Immunity, Bone, and Beyond
Discovery and characterization of the cytokine receptor-cytokine-decoy receptor triad formed by RANKL-RANK-OPG have led not only to immense advances in understanding the biology of bone homeostasis, but have also crystalized appreciation of the critical regulatory relationship that exists between bone and immunity, resulting in the emergence of the burgeoning field of osteoimmunology. RANKL-RANK-OPG are members of the tumor necrosis factor (TNF) and TNF receptor superfamilies, and share signaling characteristics common to many members of each. Developmentally regulated and cell-type specific expression patterns of each of these factors have revealed key regulatory functions for RANKL-RANK-OPG in bone homeostasis, organogenesis, immune tolerance and cancer. Successful efforts at designing and developing therapeutic agents targeting RANKL-RANK-OPG have been undertaken for osteoporosis, and additional efforts are underway for other conditions. In this review, we will summarize the basic biology of the RANKL-RANK-OPG system, relate its cell-type specific functions to system-wide mechanisms of development and homeostasis, and highlight emerging areas of interest for this cytokine group.
Mathematical Modeling of Spatio-Temporal Dynamics of a Single Bone Multicellular Unit
Abstract During bone remodeling, bone-resorbing osteoclasts and bone-forming osteoblasts are organized in bone multicellular units (BMUs), which travel at a rate of 20–40 μm/d for 6–12 mo, maintaining a cylindrical structure. However, the interplay of local BMU geometry with biochemical regulation is poorly understood. We developed a mathematical model of BMU describing changes in time and space of the concentrations of proresorptive cytokine RANKL and its inhibitor osteoprotegerin (OPG), in osteoclast and osteoblast numbers, and in bone mass. We assumed that osteocytes surrounding a microfracture produce RANKL, which attracted osteoclasts. OPG and RANKL were produced by osteoblasts and diffused through bone, RANKL was eliminated by binding to OPG and RANK. Osteoblasts were coupled to osteoclasts through paracrine factors. The evolution of the BMU arising from this model was studied using numerical simulations. Our model recapitulated the spatio-temporal dynamics observed in vivo in a cross-section of bone. In response to a RANKL field, osteoclasts moved as a well-confined cutting cone. The coupling of osteoclasts to osteoblasts allowed for sufficient recruitment of osteoblasts to the resorbed surfaces. The RANKL field was the highest at the microfracture in front of the BMU, whereas the OPG field peaked at the back of the BMU, resulting in the formation of a RANKL/OPG gradient, which strongly affected the rate of BMU progression and its size. Thus, the spatial organization of a BMU provides important constraints on the roles of RANKL and OPG as well as possibly other regulators in determining the outcome of remodeling in the BMU.
Osteoclast differentiation and activation
Osteoclasts are specialized cells derived from the monocyte/macrophage haematopoietic lineage that develop and adhere to bone matrix, then secrete acid and lytic enzymes that degrade it in a specialized, extracellular compartment. Discovery of the RANK signalling pathway in the osteoclast has provided insight into the mechanisms of osteoclastogenesis and activation of bone resorption, and how hormonal signals impact bone structure and mass. Further study of this pathway is providing the molecular basis for developing therapeutics to treat osteoporosis and other diseases of bone loss.
Osteoprotegerin in Bone Metastases: Mathematical Solution to the Puzzle
Bone is a common site for cancer metastasis. To create space for their growth, cancer cells stimulate bone resorbing osteoclasts. Cytokine RANKL is a key osteoclast activator, while osteoprotegerin (OPG) is a RANKL decoy receptor and an inhibitor of osteoclastogenesis. Consistently, systemic application of OPG decreases metastatic tumor burden in bone. However, OPG produced locally by cancer cells was shown to enhance osteolysis and tumor growth. We propose that OPG produced by cancer cells causes a local reduction in RANKL levels, inducing a steeper RANKL gradient away from the tumor and towards the bone tissue, resulting in faster resorption and tumor expansion. We tested this hypothesis using a mathematical model of nonlinear partial differential equations describing the spatial dynamics of OPG, RANKL, PTHrP, osteoclasts, tumor and bone mass. We demonstrate that at lower expression rates, tumor-derived OPG enhances the chemotactic RANKL gradient and osteolysis, whereas at higher expression rates OPG broadly inhibits RANKL and decreases osteolysis and tumor burden. Moreover, tumor expression of a soluble mediator inducing RANKL in the host tissue, such as PTHrP, is important for correct orientation of the RANKL gradient. A meta-analysis of OPG, RANKL and PTHrP expression in normal prostate, carcinoma and metastatic tissues demonstrated an increase in expression of OPG, but not RANKL, in metastatic prostate cancer, and positive correlation between OPG and PTHrP in metastatic prostate cancer. The proposed mechanism highlights the importance of the spatial distribution of receptors, decoys and ligands, and can be applied to other systems involving regulation of spatially anisotropic processes.
The Role of Osteocytes in Targeted Bone Remodeling: A Mathematical Model
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.
The Effect of Inflammation on Bone
Bone remodeling is the continual process to renew the adult skeleton through the sequential action of osteoblasts and osteoclasts. Nuclear factor RANK, an osteoclast receptor, and its ligand RANKL, expressed on the surface of osteoblasts, result in coordinated control of bone remodeling. Inflammation, a feature of illness and injury, plays a distinct role in skewing this process toward resorption. It does so via the interaction of inflammatory mediators and their related peptides with osteoblasts and osteoclasts, to alter the expression of RANK and RANKL. Such chemical mediators include TNFa, glucocorticoids, histamine, bradykinin, PGE2, systemic RANKL from immune cells, and interleukins 1 and 6. A thorough understanding of bone response to injury and disease, and ability to detect such biomarkers, as well as imaging to identify early structural and mechanical property changes in bone architecture, is important in improving management and outcomes of bone related pathology. While gut health and vitamin and mineral availability appear vitally important, there are very few intervention strategies currently available to favorably alter bone pathology induced by inflammation. Further research is required in this field to advance early detection and treatments.
The Expression of Osteoprotegerin and RANK Ligand and the Support of Osteoclast Formation by Stromal-Osteoblast Lineage Cells Is Developmentally Regulated**This work was supported by Grant AG-04875 from the National Institute on Aging.
Abstract. The one or more molecular mechanisms that determine the obligatory sequence of resorption followed by formation during bone remodeling is unclear
Complex Dynamics of Osteoclast Formation and Death in Long-Term Cultures
BackgroundOsteoclasts, cells responsible for bone resorption, contribute to the development of degenerative, metabolic and neoplastic bone diseases, which are often characterized by persistent changes in bone microenvironment. We aimed to investigate the dynamics of osteoclast formation and death in cultures that considerably exceeded the length of standard protocol and to design a mathematical model describing osteoclastogenesis.Methodology/Principal FindingsRAW 264.7 monocytic cells fuse to form multinucleated osteoclasts upon treatment with pro-resorptive cytokine RANKL. We have found that in long-term experiments (15–26 days), the dynamics of changes in osteoclast numbers was remarkably complex and qualitatively variable in different experiments. Whereas 19 of 46 experiments exhibited single peak of osteoclast formation, in 27 experiments we observed development of successive waves of osteoclast formation and death. Periodic changes in osteoclast numbers were confirmed in long-term cultures of mouse bone marrow cells treated with M-CSF and RANKL. Because the dynamics of changes in osteoclast numbers was found to be largely independent of monocytes, a two-species model of ordinary differential equations describing the changes in osteoclasts and monocytes was ineffective in recapitulating the oscillations in osteoclast numbers. Following experimental observation that medium collected from mature osteoclasts inhibited osteoclastogenesis in fresh cultures, we introduced a third variable, factor f, to describe osteoclast-derived inhibitor. This model allowed us to simulate the oscillatory changes in osteoclasts, which were coupled to oscillatory changes in the factor f, whereas monocytes changed exponentially. Importantly, to achieve the experimentally observed oscillations with increasing amplitude, we also had to assume that osteoclast presence stimulates osteoclast formation.Conclusions/SignificanceThis study identifies the critical role for osteoclast autocrine regulation in controlling long-term dynamic of osteoclast formation and death and describes the complementary roles for negative and positive feedback mediators in determining the sharp dynamics of activation and inactivation of osteoclasts.
A review of mathematical modeling of bone remodeling from a systems biology perspective
Bone remodeling is an essential physiological process in the adult skeleton. Due to the complex nature of this process, many mathematical models of bone remodeling have been developed. Each of these models has unique features, but they have underlying patterns. In this review, the authors highlight the important aspects frequently found in mathematical models for bone remodeling and discuss how and why these aspects are included when considering the physiology of the bone basic multicellular unit, which is the term used for the collection of cells responsible for bone remodeling. The review also emphasizes the view of bone remodeling from a systems biology perspective. Understanding the systemic mechanisms involved in remodeling will help provide information on bone pathology associated with aging, endocrine disorders, cancers, and inflammatory conditions and enhance systems pharmacology. Furthermore, some features of the bone remodeling cycle and interactions with other organ systems that have not yet been modeled mathematically are discussed as promising future directions in the field.
A review of mathematical modeling of bone remodeling from a systems biology perspective
Bone remodeling is an essential, delicately balanced physiological process of coordinated activity of bone cells that remove and deposit new bone tissue in the adult skeleton. Due to the complex nature of this process, many mathematical models of bone remodeling have been developed. Each of these models has unique features, but they have underlying patterns. In this review, the authors highlight the important aspects frequently found in mathematical models for bone remodeling and discuss how and why these aspects are included when considering the physiology of the bone basic multicellular unit, which is the term used for the collection of cells responsible for bone remodeling. The review also emphasizes the view of bone remodeling from a systems biology perspective. Understanding the systemic mechanisms involved in remodeling will help provide information on bone pathology associated with aging, endocrine disorders, cancers, and inflammatory conditions and enhance systems pharmacology. Furthermore, some features of the bone remodeling cycle and interactions with other organ systems that have not yet been modeled mathematically are discussed as promising future directions in the field.
Toward a Mathematical Modeling of Diseases’ Impact on Bone Remodeling: Technical Review
A wide variety of bone diseases have hitherto been discovered, such as osteoporosis, Patget’s disease, osteopetrosis, and metastatic bone disease, which is not well defined. Some of these diseases are secondary to other pathologies, including cancer, or to some clinical treatments. To better understand bone behavior and prevent its deterioration, bone biomechanics have been the subject of mathematical modeling that exponentially increased over the last years. These models are more and more involving the impact of bone diseases on its quality. The current paper provides a meaningful and critical analysis of previously developed bone remodeling mathematical models, particularly those addressing bone diseases. Besides, mechanistic pharmacokinetic/pharmacodynamic (PK/PD) models, which englobe either bone disease and its treatments’ effect on bone health. Therefore, the review starts by presenting bone remodeling cycle and mathematical models describing this process, followed by introducing some bone diseases and discussing models of pathological mechanisms affecting bone, and ends by exhibiting the available bone treatment procedures and the PK/PD models considering these lasts.
Analytic approach to explore dynamical osteoporotic bone turnover
The dynamics of the osteoporotic bone turnover is studied in this paper with the aid of stability analysis of the associated mathematical model. Osteoporosis, which is a common bone disorder, is studied in this papper in detail with an emphasis on the relative threshold values. We examine the expository signaling among the bone cells named osteoclast and osteoblast. Main functioning of osteoblasts is bone formation, whereas osteoclasts are bone removal cells.
Dynamic Biochemical and Cellular Models of Bone Physiology: Integrating Remodeling Processes, Tumor Growth, and Therapy
Bone is an activeCoelho, Rui M. Neto, Joana P. connective tissue composed of different types of cells. The dynamic behavior of bone remodeling processes is typically represented throughValério, Duarte differential equations, which represent the physiological phenomena occurring in this organ. These models takeVinga, Susana into account the tight biochemical regulation between osteoclasts and osteoblasts and have also been enriched with variables and parameters related to bone pathologies and treatment. This chapter reviews some of the more recent models describing bone physiology, focusing on those that include the main cellular processes, along the biochemical control, and also the pharmacokinetic/pharmacodynamic (PK/PD) of the most common treatments for diseases such as cancer. These models are then compared in terms of the simulations obtained and, finally, some highlights on integrating them with the biomechanical component of the system which will be given. These models are expected to provide a valuable insight into this complex system and to support the development of clinical decision systems for bone pathologies.
Osteoporosis in Rheumatoid Arthritis: Dangerous Liaisons
Osteoporosis has been classically considered a comorbidity of rheumatoid arthritis (RA). However, recent advances in the pathogenesis of osteoporosis in RA have shown a close interplay between cells of the immune system and those involved in bone remodeling, introducing new actors into the classic route in which osteoclast activation is related to the RANK/RANKL/OPG pathway. In fact, the inflammatory state in early stages of RA, mediated by interleukin (IL)-1, IL-6, IL-8 and tumour necrosis factor (TNF)-α has the ability to activate and differentiate osteoclasts not only through their relationship with RANKL, but also through the Wnt/DKK1/sclerostin pathway, leading to bone loss. The role of synovial fibroblasts and activated T lymphocytes in the expression of the RANKL system and its connection to bone destruction is also depicted. In addition, autoantibodies such as rheumatoid factor and anti-citrullinated protein antibodies are other pathogenic mechanisms for the development of bone erosions and systemic osteoporosis in RA, even before the onset of arthritis. The aim of this review is to unravel the relationship between different factors involved in the development of osteoporosis in RA patients, both the classic factors and the most novel, based on the relationship of autoantibodies with bone remodeling. Furthermore, we propose that bone mineral density measured by different techniques may be helpful as a biomarker of severity in early arthritis patients.
Mathematical modeling of postmenopausal osteoporosis and its treatment by the anti‐catabolic drug denosumab
SUMMARY Denosumab, a fully human monoclonal antibody, has been approved for the treatment of postmenopausal osteoporosis. The therapeutic effect of denosumab rests on its ability to inhibit osteoclast differentiation. Here, we present a computational approach on the basis of coupling a pharmacokinetics model of denosumab with a pharmacodynamics model for quantifying the effect of denosumab on bone remodeling. The pharmacodynamics model comprises an integrated systems biology‐continuum micromechanics approach, including a bone cell population model, considering the governing biochemical factors of bone remodeling (including the action of denosumab), and a multiscale micromechanics‐based bone mechanics model, for implementing the mechanobiology of bone remodeling in our model. Numerical studies of postmenopausal osteoporosis show that denosumab suppresses osteoclast differentiation, thus strongly curtailing bone resorption. Simulation results also suggest that denosumab may trigger a short‐term bone volume gain, which is, however, followed by constant or decreasing bone volume. This evolution is accompanied by a dramatic decrease of the bone turnover rate by more than one order of magnitude. The latter proposes dominant occurrence of secondary mineralization (which is not anymore impeded through cellular activity), leading to higher mineral concentration per bone volume. This explains the overall higher bone mineral density observed in denosumab‐related clinical studies. Copyright © 2013 John Wiley & Sons, Ltd.
MODEL-BASED ANALYSIS OF IGF-1 EFFECT ON OSTEOBLAST AND OSTEOCLAST REGULATION IN BONE TURNOVER
The main determinant of bone Ca accretion is a bimolecular regulatory network on osteoblast (OB) and osteoclast (OC). Even though IGF-1 is known as an important regulator in bone cell cycle, little has been done to model IGF-1 action in bone cell regulation. Thus, the objective is to develop a mathematical model that depicts the regulatory action of IGF-1 onto the OB and OC interaction, and to evaluate adolescent and adult bone Ca accretion in response to differences in IGF-1 levels. As a result, a dynamic model of OB and OC with two main regulatory systems, i.e., Receptor Activator for Nuclear Factor [Formula: see text]B (RANK)-RANK Ligand (RANKL)-osteoprogerin (OPG) system, and TGF-[Formula: see text], was augmented with the IGF-1, and incorporated into Ca kinetic data to predict exchangeable bone Ca. The developed model could predict a change in OB and OC levels in response to perturbations in regulators, producing results consistent with bone physiology and published experimental data. The model also estimated parametric difference in regulators between adults and adolescents, suggesting that RANKL/OPG in adolescents was about 4 times higher than in adults, while adolescent serum PTH and IGF-1 concentrations were 60% and 220% of those of adults, respectively. This study highlighted the influence of IGF-1 on the regulation of bone cells in positively modulating bone Ca, suggesting that IGF-1 may be an effective target for reducing bone loss by promoting mature OB.