Abstract

Purpose : Radon risks derive from exposure of bronchio-epithelial cells to high-linear energy transfer (LET) α -particles. α -particle exposure can result in bystander effects, where irradiated cells emit signals resulting in damage to nearby unirradiated bystander cells. This can result in non-linear dose-response relations, and inverse dose-rate effects. Domestic radon risk estimates are currently extrapolated from miner data, which are at both higher doses and higher dose-rates, so bystander effects on unhit cells could play a large role in the extrapolation of risks from mines to homes. Therefore, we extend an earlier quantitative mechanistic model of bystander effects to include protracted exposure, with the aim of quantifying the significance of the bystander effect for very prolonged exposures. Materials and methods : A model of high-LET bystander effects, originally developed to analyse oncogenic transformation in vitro, is extended to low dose-rates. The model considers radiation response as a superposition of bystander and linear direct e It attributes bystander effects to a small subpopulation of hypersensitive cells, with the bystander contribution dominating the direct contribution at very low acute doses but saturating as the dose increases. Inverse dose-rate effects are attributed to the replenishment of the hypersensitive subpopulation during prolonged irradiation. Results : The model was fitted to dose- and dose-rate-dependent radon-exposed miner data, suggesting that one directly hit target bronchio-epithelial cell can send bystander signals to about 50 neighbouring target cells. The model suggests that a naïve linear extrapolation of radon miner data to low doses, without accounting for dose-rate, would result in an underestimation of domestic radon risks by about a factor of 4, a value comparable with the empirical estimate applied in the recent BEIR-VI report on radon risk estimation. Conclusions : Bystander effects represent a plausible quantitative and mechanistic explanation of inverse dose-rate effects by high-LET radiation, resulting in non-linear dose-response relations and a complex interplay between the effects of dose and exposure time. The model presented provides a potential mechanistic underpinning for the empirical exposure-time correction factors applied in the recent BEIR-VI for domestic radon risk estimation.

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