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Predicting Long-Term Asbestos Prevalence in Human Lungs, Lymph Nodes, and Remote Organs from Short-Term Murine Experiments

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Abstract

Inhalation of asbestos fibers leads to a suite of fatal diseases that can manifest years, if not decades, after cessation of exposure. The first phase of disease progression occurs as fibers are transported from point of entry in the lungs throughout the entire body. A mathematical model is developed for the disposition of non-chrysotile asbestos in the body and, except for exposure levels, is parameterized by published data on short-term rat experiments. Asbestos exposure in individual humans is determined by matching published long-term lung data for nine patients. The resulting model predicts transport of fibers within the lymphatic system and prevalence of fibers in lymph nodes for these patients with reasonable accuracy. Model predictions for remote organs are compared against published observations. The model consists of a system of globally stable differential equations, and a sensitivity analysis was conducted. The model indicates that fiber density in lymph nodes is correlated with total exposure, level times duration, no matter whether there is a long-term, low-level exposure or short-term, high-level exposure. The model predicts that levels of sequestered asbestos reach steady state within five years of cessation of exposure, a timeline previously not known. The model suggests that the time to steady state is short compared to onset of disease, and that delayed onset of related disease may be a function of chemical and biological processes not in this model.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, College of the Holy Cross, Worcester, MA, 01610, USA

    Alisa DeStefano

  2. Mathematics and Statistics Department, Texas Tech University, Lubbock, TX, 79409, USA

    Clyde Martin

  3. Lyme, NH, USA

    Andrew Huang

  4. Department of Mathematics, Dartmouth College, Hanover, NH, 03755, USA

    Dorothy Wallace

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  1. Alisa DeStefano
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  2. Clyde Martin
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  3. Andrew Huang
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  4. Dorothy Wallace
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Correspondence to Alisa DeStefano.

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DeStefano, A., Martin, C., Huang, A. et al. Predicting Long-Term Asbestos Prevalence in Human Lungs, Lymph Nodes, and Remote Organs from Short-Term Murine Experiments. Bull Math Biol 83, 54 (2021). https://doi.org/10.1007/s11538-021-00882-8

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