Interaction of low dose radiation and other factors

Individual response of humans to ionising radiation: governing factors and importance for radiological protection

Tissue reactions and stochastic effects after exposure to ionising radiation are variable between individuals but the factors and mechanisms governing individual responses are not well understood. Individual responses can be measured at different levels of biological organization and using different endpoints following varying doses of radiation, including: cancers, non-cancer diseases and mortality in the whole organism; normal tissue reactions after exposures; and, cellular endpoints such as chromosomal damage and molecular alterations. There is no doubt that many factors influence the responses of people to radiation to different degrees. In addition to the obvious general factors of radiation quality, dose, dose rate and the tissue (sub)volume irradiated, recognized and potential determining factors include age, sex, life style (e.g., smoking, diet, possibly body mass index), environmental factors, genetics and epigenetics, stochastic distribution of cellular events, and systemic comorbidities such as diabetes or viral infections. Genetic factors are commonly thought to be a substantial contributor to individual response to radiation. Apart from a small number of rare monogenic diseases such as ataxia telangiectasia, the inheritance of an abnormally responsive phenotype among a population of healthy individuals does not follow a classical Mendelian inheritance pattern. Rather it is considered to be a multi-factorial, complex trait.

Cancer risk at low doses of ionizing radiation: artificial neural networks inference from atomic bomb survivors

Cancer risk at low doses of ionizing radiation remains poorly defined because of ambiguity in the quantitative link to doses below 0.2 Sv in atomic bomb survivors in Hiroshima and Nagasaki arising from limitations in the statistical power and information available on overall radiation dose. To deal with these difficulties, a novel nonparametric statistics based on the 'integrate-and-fire' algorithm of artificial neural networks was developed and tested in cancer databases established by the Radiation Effects Research Foundation. The analysis revealed unique features at low doses that could not be accounted for by nominal exposure dose, including (i) the presence of a threshold that varied with organ, gender and age at exposure, and (ii) a small but significant bumping increase in cancer risk at low doses in Nagasaki that probably reflects internal exposure to (239)Pu. The threshold was distinct from the canonical definition of zero effect in that it was manifested as negative excess relative risk, or suppression of background cancer rates. Such a unique tissue response at low doses of radiation exposure has been implicated in the context of the molecular basis of radiation-environment interplay in favor of recently emerging experimental evidence on DNA double-strand break repair pathway choice and its epigenetic memory by histone marking.