Osteoarthritis (OA) is a debilitating joint disease characterized by articular cartilage degradation, inflammation and pain. An extensive range of in vivo and in vitro studies evidences that mechanical loads induce changes in chondrocyte gene expression, through a process known as mechanotransduction. It involves cascades of complex molecular interactions that convert physical signals into cellular response(s) that favor either chondroprotection or cartilage destruction. Systematic representations of those interactions can positively inform early strategies for OA management, and dynamic modelling allows semi-quantitative representations of the steady states of complex biological system according to imposed initial conditions. Yet, mechanotransduction is rarely integrated. Hence, a novel mechano-sensitive network-based model is proposed, in the form of a continuous dynamical system: an interactome of a set of 118 nodes, i.e., mechano-sensitive cellular receptors, second messengers, transcription factors and proteins, related among each other through a specific topology of 358 directed edges is developed. Results show that under physio-osmotic initial conditions, an anabolic state is reached, whereas initial perturbations caused by pro-inflammatory and injurious mechanical loads leads to a catabolic profile of node expression. More specifically, healthy chondrocyte markers (Sox9 and CITED2) are fully expressed under physio-osmotic conditions, and reduced under inflammation, or injurious loadings. In contrast, NF-κB and Runx2, characteristic of an osteoarthritic chondrocyte, become activated under inflammation or excessive loading regimes. A literature-based evaluation shows that the model can replicate 94% of the experiments tested. Sensitivity analysis based on a factorial design of a treatment shows that inflammation has the strongest influence on chondrocyte metabolism, along with a significant deleterious effect of static compressive loads. At the same time, anti-inflammatory therapies appear as the most promising ones, though the restoration of structural protein production seems to remain a major challenge even in beneficial mechanical environments. The newly developed mechano-sensitive network model for chondrocyte activity reveals a unique potential to reflect load-induced chondroprotection or articular cartilage degradation in different mechano-chemical-environments.

/pdf/network-based-modelling-of-mechano-inflammatory-chondrocyte-2h0y0fc1.pdf

Network-based modelling of mechano-inflammatory chondrocyte regulation in early osteoarthritis

A chemo-mechano-biological modeling framework for cartilage evolving in health, disease, injury, and treatment

Current methodologies to estimate cell responses usually focus on bottom-up intracellular network modeling, accompanied by limitations regarding the network topology and regarding the consideration of transient changes in cell responses due to chronic, dose-dependent stimulus exposure. Here we present a novel high-level top-down network modelling approach to simulate dose- and time-dependent cell responses within heterogeneous multifactorial, multicellular environments. Through the representation of cell activities as time-dependent parallel networks (PNt), the PNt-Methodology provides relative, interrelated cell responses for heterogeneous stimulus environments. The methodology is based on a systematic use of experimental findings, both data- and knowledge-based. Applied to intervertebral disc multicellular systems, the PNt-Methodology allows for the first time to obtain qualitatively validated cell responses for daily human moving activities and exposure to microgravity. The PNt-Methodology is not tissue specific per-se and is designed to be easily scalable. Eventually, it provides a one-of-a-kind network modeling approach to approximate complex multicellular systems.

The PNt-Methodology: a top-down network modelling approach to estimate dose- and time-dependent cell responses to complex multifactorial environments

Osteoarthritis (OA) is a chronic joint disease with increasing prevalence. Chondrocytes (CHs) are highly differentiated end-stage cells with a secretory phenotype that keeps the extracellular matrix (ECM) balanced and the cartilage environment stable. Osteoarthritis dedifferentiation causes cartilage matrix breakdown, accounting for one of the key pathogenesis of osteoarthritis. Recently, the activation of transient receptor potential ankyrin 1 (TRPA1) was claimed to be a risk factor in osteoarthritis by causing inflammation and extracellular matrix degradation. However, the underlying mechanism is still unknown. Due to its mechanosensitive property, we speculated that the role of TRPA1 activation during osteoarthritis is matrix stiffness-dependent. In this study, we cultured the chondrocytes from patients with osteoarthritis on stiff vs. soft substrates, treated them with allyl isothiocyanate (AITC), a transient receptor potential ankyrin 1 agonist, and compared the chondrogenic phenotype, containing cell shape, F-actin cytoskeleton, vinculin, synthesized collagen profiles and their transcriptional regulatory factor, and inflammation-related interleukins. The data suggest that allyl isothiocyanate treatment activates transient receptor potential ankyrin 1 and results in both positive and harmful effects on chondrocytes. In addition, a softer matrix could help enhance the positive effects and alleviate the harmful ones. Thus, the effect of allyl isothiocyanate on chondrocytes is conditionally controllable, which could be associated with transient receptor potential ankyrin 1 activation, and is a promising strategy for osteoarthritis treatment.

The effect of allyl isothiocyanate on chondrocyte phenotype is matrix stiffness-dependent: Possible involvement of TRPA1 activation

Osteoarthritis (OA) is a joint disorder characterized by progressive degeneration of cartilage extracellular matrix (ECM), chondrocyte hypertrophy and apoptosis and inflammation. The current treatments mainly concern pain control and reduction of inflammation, but no therapeutic strategy has been identified as a disease-modifying treatment. Therefore, identifying specific biomarkers useful to prevent, treat or distinguish the stages of OA disease has become an immediate need of clinical practice. The role of microRNAs (miRNAs) in OA has been investigated in the last decade, and increasing evidence has emerged that the influence of the environment on gene expression through epigenetic processes contributes to the development, progression and aggressiveness of OA, in particular acting on the microenvironment modulations. The effects of epigenetic regulation, particularly different miRNA methylation during OA disease, were highlighted in the present systematic review. The evidence arising from this study of the literature conducted in three databases (PubMed, Scopus, Web of Science) suggested that miRNA methylation state already strongly impacts OA progression, driving chondrocytes and synoviocyte proliferation, apoptosis, inflammation and ECM deposition. However, the possibility of understanding the mechanism by which different epigenetic modifications of miRNA or pre-miRNA sequences drive the aggressiveness of OA could be the new focus of future investigations.

Epigenetic Modifications of MiRNAs in Osteoarthritis: A Systematic Review on Their Methylation Levels and Effects on Chondrocytes, Extracellular Matrix and Joint Inflammation

In osteoarthritis (OA), chondrocyte metabolism dysregulation increases relative catabolic activity, which leads to cartilage degradation. To enable the semiquantitative interpretation of the intricate mechanisms of OA progression, we propose a network-based model at the chondrocyte level that incorporates the complex ways in which inflammatory factors affect structural protein and protease expression and nociceptive signals. Understanding such interactions will leverage the identification of new potential therapeutic targets that could improve current pharmacological treatments. Our computational model arises from a combination of knowledge-based and data-driven approaches that includes in-depth analyses of evidence reported in the specialized literature and targeted network enrichment. We achieved a mechanistic network of molecular interactions that represent both biosynthetic, inflammatory and degradative chondrocyte activity. The network is calibrated against experimental data through a genetic algorithm, and 81% of the responses tested have a normalized root squared error lower than 0.15. The model captures chondrocyte-reported behaviors with 95% accuracy, and it correctly predicts the main outcomes of OA treatment based on blood-derived biologics. The proposed methodology allows us to model an optimal regulatory network that controls chondrocyte metabolism based on measurable soluble molecules. Further research should target the incorporation of mechanical signals. 

/pdf/regulatory-network-based-model-to-simulate-the-biochemical-28elzadq.pdf

Maria Segarra-Queralt

Papers

Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments

Network-based modelling of mechano-inflammatory chondrocyte regulation in early osteoarthritis