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bioRxiv · 10.1101/2022.10.03.510677

An agent-based modeling approach for lung fibrosis in response to COVID-19

Islam, M. A.·Getz, M.·Macklin, P.·Versypt, A. N. F.
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Abstract

The severity of the COVID-19 pandemic has created an emerging need to investigate the long-term effects of infection on patients. Many individuals are at risk of suffering pulmonary fibrosis due to the pathogenesis of lung injury and impairment in the healing mechanism. Fibroblasts are the central mediators of extracellular matrix (ECM) deposition during tissue regeneration, regulated by anti-inflammatory cytokines including transforming growth factor beta (TGF-{beta}). The TGF-{beta}-dependent accumulation of fibroblasts at the damaged site and excess fibrillar collagen deposition lead to fibrosis. We developed an open-source, multiscale tissue simulator to investigate the role of TGF-{beta} sources in the progression of lung fibrosis after SARS-CoV-2 exposure, intracellular viral replication, infection of epithelial cells, and host immune response. Using the model, we predicted the dynamics of fibroblasts, TGF-{beta}, and collagen deposition for 15 days post-infection in virtual lung tissue. Our results showed variation in collagen area fractions between 2% and 40% depending on the spatial behavior of the sources (stationary or mobile), the rate of activation of TGF-{beta}, and the duration of TGF-{beta} sources. We identified M2 macrophages as primary contributors to higher collagen area fraction. Our simulation results also predicted fibrotic outcomes even with lower collagen area fraction when spatially-localized latent TGF-{beta} sources were active for longer times. We validated our model by comparing simulated dynamics for TGF-{beta}, collagen area fraction, and macrophage cell population with independent experimental data from mouse models. Our results showed that partial removal of TGF-{beta} sources changed the fibrotic patterns; in the presence of persistent TGF-{beta} sources, partial removal of TGF-{beta} from the ECM significantly increased collagen area fraction due to maintenance of chemotactic gradients driving fibroblast movement. The computational findings are consistent with independent experimental and clinical observations of collagen area fractions and cell population dynamics not used in developing the model. These critical insights into the activity of TGF-{beta} sources may find applications in the current clinical trials targeting TGF-{beta} for the resolution of lung fibrosis. Author summaryCOVID-19 survivors are at risk of lung fibrosis as a long-term effect. Lung fibrosis is the excess deposition of tissue materials in the lung that hinder gas exchange and can collapse the whole organ. We identified TGF-{beta} as a critical regulator of fibrosis. We built a model to investigate the mechanisms of TGF-{beta} sources in the process of fibrosis. Our results showed spatial behavior of sources (stationary or mobile) and their activity (activation rate of TGF-{beta}, longer activation of sources) could lead to lung fibrosis. Current clinical trials for fibrosis that target TGF-{beta} need to consider TGF-{beta} sources spatial properties and activity to develop better treatment strategies.

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Islam, M. A., Getz, M., Macklin, P., Versypt, A. N. F.. 2022-10-04. An agent-based modeling approach for lung fibrosis in response to COVID-19. https://doi.org/10.1101/2022.10.03.510677

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