Dose-response modeling of NLRP3 inflammasome-mediated diseases: asbestos, lung cancer, and malignant mesothelioma as examples

Abstract

Can a single fiber of amphibole asbestos increase the risk of lung cancer or malignant mesothelioma (MM)? Traditional linear no-threshold (LNT) risk assessment assumptions imply that the answer is yes: there is no safe exposure level. This paper draws on recent scientific progress in inflammation biology, especially elucidation of the activation thresholds for NLRP3 inflammasomes and resulting chronic inflammation, to model dose-response relationships for malignant mesothelioma and lung cancer risks caused by asbestos exposures. The modeling integrates a physiologically based pharmacokinetics (PBPK) front end with inflammation-driven two-stage clonal expansion (I-TSCE) models of carcinogenesis to describe how exposure leads to chronic inflammation, which in turn promotes carcinogenesis. Together, the combined PBPK and I-TSCE modeling predict that there are practical thresholds for exposure concentration below which asbestos exposure does not cause chronic inflammation in less than a lifetime, and therefore does not increase chronic inflammation-dependent cancer risks. Quantitative examples using model parameter estimates drawn from the literature suggest that practical thresholds may be within about a factor of 2 of some past exposure levels for some workers. The I-TSCE modeling framework explains previous puzzling aspects of asbestos epidemiology, such as why age at first exposure is a better predictor of lifetime MM risk than exposure duration. It may be a valuable tool for risk analysts when LNT assumptions are not justified due to inflammation response thresholds mediating dose-response relationships.

Keywords:

• Dose response model
• risk assessment
• threshold
• inflammation
• chronic inflammation
• asbestos

Acknowledgements

The author thanks Michael Greenberg for thoughtful suggestions and advice on exposition and tone, especially to clearly separate science and policy discussions and to explain that the main emphasis of the present paper is on the former, although scientific progress may have implications for policy. I also thank three anonymous reviewers who asked useful and challenging questions about the dose levels at which in vitro results were (and were not) seen, and about prospects for linking the theory and model presented here to specific fiber concentration data for human workers. Their comments, questions, and suggestions helped to shape and improve the final paper.

Declaration of interest

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Development of the risk modeling approach reported here was supported in part by the following contract research projects undertaken by the author’s employer, Cox Associates LLC: (1) A multiyear applied research program funded by the National Stone, Sand, and Gravel Association (NSSGA) in 2017-2019 on modeling the human health risks from respirable crystalline silica (RCS), elongated mineral particles, and asbestos, including a project to develop the integrated computational model of pharmacokinetics, pharmacodynamics, and lung cancer risk presented here. (2) A collaboration with the George Washington University Regulatory Studies Center, supported in part by funding from the Searle Freedom Trust for applied research on “Improving the Economic and Scientific Analysis of Regulations.” All aspects of this article, including the research questions addressed, the methods developed and applied, and the conclusions reached, are solely the author’s, and no funder or third parties reviewed or commented on the work prior to its submission.