PLoS Computational Biology (Jan 2023)

Injury-related cell death and proteoglycan loss in articular cartilage: Numerical model combining necrosis, reactive oxygen species, and inflammatory cytokines

  • Joonas P. Kosonen,
  • Atte S. A. Eskelinen,
  • Gustavo A. Orozco,
  • Petteri Nieminen,
  • Donald D. Anderson,
  • Alan J. Grodzinsky,
  • Rami K. Korhonen,
  • Petri Tanska

Journal volume & issue
Vol. 19, no. 1

Abstract

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Osteoarthritis (OA) is a common musculoskeletal disease that leads to deterioration of articular cartilage, joint pain, and decreased quality of life. When OA develops after a joint injury, it is designated as post-traumatic OA (PTOA). The etiology of PTOA remains poorly understood, but it is known that proteoglycan (PG) loss, cell dysfunction, and cell death in cartilage are among the first signs of the disease. These processes, influenced by biomechanical and inflammatory stimuli, disturb the normal cell-regulated balance between tissue synthesis and degeneration. Previous computational mechanobiological models have not explicitly incorporated the cell-mediated degradation mechanisms triggered by an injury that eventually can lead to tissue-level compositional changes. Here, we developed a 2-D mechanobiological finite element model to predict necrosis, apoptosis following excessive production of reactive oxygen species (ROS), and inflammatory cytokine (interleukin-1)-driven apoptosis in cartilage explant. The resulting PG loss over 30 days was simulated. Biomechanically triggered PG degeneration, associated with cell necrosis, excessive ROS production, and cell apoptosis, was predicted to be localized near a lesion, while interleukin-1 diffusion-driven PG degeneration was manifested more globally. Interestingly, the model also showed proteolytic activity and PG biosynthesis closer to the levels of healthy tissue when pro-inflammatory cytokines were rapidly inhibited or cleared from the culture medium, leading to partial recovery of PG content. The numerical predictions of cell death and PG loss were supported by previous experimental findings. Furthermore, the simulated ROS and inflammation mechanisms had longer-lasting effects (over 3 days) on the PG content than localized necrosis. The mechanobiological model presented here may serve as a numerical tool for assessing early cartilage degeneration mechanisms and the efficacy of interventions to mitigate PTOA progression. Author summary Osteoarthritis is one of the most common musculoskeletal diseases. When osteoarthritis develops after a joint injury, it is designated as post-traumatic osteoarthritis. A defining feature of osteoarthritis is degeneration of articular cartilage, which is partly driven by cartilage cells after joint injury, and further accelerated by inflammation. The degeneration triggered by these biomechanical and biochemical mechanisms is currently irreversible. Thus, early prevention/mitigation of disease progression is a key to avoiding PTOA. Prior computational models have been developed to provide insights into the complex mechanisms of cartilage degradation, but they rarely include cell-level cartilage degeneration mechanisms. Here, we present a novel approach to simulate how the early post-traumatic biomechanical and inflammatory effects on cartilage cells eventually influence tissue composition. Our model includes the key regulators of early post-traumatic osteoarthritis: chondral lesions, cell death, reactive oxygen species, and inflammatory cytokines. The model is supported by several experimental explant culture findings. Interestingly, we found that when post-injury inflammation is mitigated, cartilage composition can partially recover. We suggest that mechanobiological models including cell–tissue-level mechanisms can serve as future tools for evaluating high-risk lesions and developing new intervention strategies.