Towards in silico Models of the Inflammatory Response in Bone Fracture Healing

Abstract

In silico modeling is a powerful strategy to investigate the biological events occurring at tissue, cellular and subcellular level during bone fracture healing. However, most current models do not consider the impact of the inflammatory response on the later stages of bone repair. Indeed, as initiator of the healing process, this early phase can alter the regenerative outcome: if the inflammatory response is too strongly down- or upregulated, the fracture can result in a non-union. This review covers the fundamental information on fracture healing, in silico modeling and experimental validation. It starts with a description of the biology of fracture healing, paying particular attention to the inflammatory phase and its cellular and subcellular components. We then discuss the current state-of-the-art regarding in silico models of the immune response in different tissues as well as the bone regeneration process at the later stages of fracture healing. Combining the aforementioned biological and computational state-of-the-art, continuous, discrete and hybrid modeling technologies are discussed in light of their suitability to capture adequately the multiscale course of the inflammatory phase and its overall role in the healing outcome. Both in the establishment of models as in their validation step, experimental data is required. Hence, this review provides an overview of the different in vitro and in vivo set-ups that can be used to quantify cell- and tissue-scale properties and provide necessary input for model credibility assessment. In conclusion, this review aims to provide hands-on guidance for scientists interested in building in silico models as an additional tool to investigate the critical role of the inflammatory phase in bone regeneration.

Keywords: bone regeneration; experimental validation; fracture healing; in silico modeling; inflammatory response; multiscale approach.

FIGURE 1

Bone fracture healing process. Timeline of secondary bone healing phases: inflammation, repair and remodeling. Tissue, cellular and subcellular levels are represented. Inflammation (left): hematoma formation triggers the invasion of inflammatory cells (neutrophils, monocytes and macrophages) and the release of pro-inflammatory (IL-1, IL-6, TNF-α) and anti-inflammatory (IL-4, IL-10, IL-11, IL-13) cytokines. Unactivated macrophages differentiate into classical (M1) and alternative (M2) activated macrophages. Repair (center): revascularization (endothelial cells), soft callus formation (fibrocartilage) and subsequent hard callus formation (woven bone) are regulated by repair cells (SPCs, fibroblasts, chondrocytes and osteoblasts) and growth factors (VEGF, FGF, BMP, TGF-β). Remodeling (right): restoration of the bone original shape by osteoblasts, osteocytes and osteoclasts, regulated by RANKL/OPG balance. These three phases are not rigidly defined over the timeline but overlap, as represented by the curves at the bottom of the image.

FIGURE 2

In silico approaches to model the bone healing process and the inflammatory response. (A) Overview of in silico techniques to describe biological processes and predict their different outcomes. The choice of the in silico model depends on the research goal. Continuous models are often used to describe general dynamics at tissue and cellular scales, such as bone mechanics, in which different tissue matrices interplay (figure adapted from Wang and Yang, 2018). Discrete models are mostly used to represent individual behavior at (sub)cellular scales, such as the immune response, which comprises a high number of cells and cytokines. The hybrid approach combines the advantages of both continuous and discrete techniques, providing comprehensive multiscale models that allow to investigate, for instance, sprouting angiogenesis during the bone regeneration process (figure obtained with the model described in Carlier et al., 2016). (B) Flow diagram summarizing the macrophage-mediated inflammation in bone fracture healing described in Trejo et al. (2019). Cells are represented by squares: unactivated macrophages (M₀), classical macrophages (M₁), alternative macrophages (M₂), SPCs (c _m ) and osteoblasts (c _b ). Pro-inflammatory (c₁) and anti-inflammatory (c₂) cytokines are represented by circles. Tissue matrices are represented by hexagons: fibrocartilage (m _c ) and woven bone (m _b ). Debris (D) is represented by a diamond. Adapted from Trejo et al. (2019).

FIGURE 3

Validation of in silico models of the inflammatory response in bone healing. (A) Summary of in vitro and in vivo experimental techniques to validate the predictive capacity of in silico models. The choice of the experimental model depends whether the validation regards a specific mechanism or the global response. In vitro models investigate single biological mechanisms, such as the chemoattractant effect of inflammatory markers or specific cell types. In vivo models evaluate the effects of individual factors, such as the depletion of a cell type, on the complete biological response. (B) Experimental techniques for the validation of in silico models can be broadly divided into cell and tissue-scale techniques. The former validate in silico models of molecular mechanisms regulating cell function and models of cell migration dynamics. The latter validate in silico models of the repair and remodeling phase, by quantifying bone histomorphometric parameters, and models describing cellular composition in the fracture site.