Application of Bayesian inference to characterize risks associated with low doses of low-LET radiation

Improved risk characterization for stochastic biological effects of low dos es of low-LET radiation is important for protecting nuclear workers and the public from harm from radiation exposure. Here we present a Bayesian appro ach to characterize risks of stochastic effects from low doses of low-LET r adiation. The stochastic effect considered is neoplastic transformation of cells because it relates closely to cancer induction. We have used a publis hed model of neoplastic transformation called NEOTRANS(1). It is based on t wo different classes of cellular sensitivity for asynchronous, exponentiall y growing populations (in vitro). One sensitivity class is the hypersensiti ve cell; the other is the resistant cell. NEOTRANS(1) includes the effects of genomic damage accumulation, DNA repair during cell cycle arrest, and DN A misrepair (non-lethal repair errors). The model-associated differential e quations are solved for conditions of in vitro irradiation at a fixed rate. Previously published solutions apply only to high dose rates and were inco rrectly assumed to apply to only high-LET radiation. Solutions provided her e apply to any fixed dose rate and to both high- and low-LET radiations. Ma rkov chain Monte Carlo methods are used to carry out the Bayesian inference of the low-dose risk for neoplastic transformation of aneuploid C3H 10T1/2 cells for X-ray doses from 0 to 1000 mGy. We have assumed that for this lo w-dose range only the hypersensitive fraction of the cells are affected. Ou r results indicate that the initial slope of the risk vs dose relationship for neoplastic transformation is as follows: (1) directly proportional to t he fraction, fl, of hypersensitive cells; (2) directly proportional to the radiosensitivity of the genomic target; and (3) inversely proportional to t he rate at which hypersensitive cells with radiation-induced damage are com mitted to undergo correct repair of genomic damage. Further, our results in dicate that very fast molecular events are associated with the commitment o f cells to the correct repair pathway. Results also indicate a relatively l arge probability for misrepair that leads to genomic instability. Our resul ts are consistent with the view that for very low doses, dose rate is not a n important variable for characterizing low-LET radiation risks so long as age-related changes in sensitivity do not occur during irradiation. (C) 200 1 Society for Mathematical Biology.