Overview of the Low Dose Radiation
Research Program

The DOE Low Dose Radiation Research Program is funding basic research to determine the responses induced by radiation exposures at doses of 10cGy and below. The research is international in nature and will provide a scientific underpinning for future radiation protection standards. Currently about 60% of the projects are funded through Universities and 30% through DOE National Laboratories. The funding is focused to determine the mechanistic basis for the interaction of low doses of radiation with biological systems. These mechanistic studies are focused on DNA damage and repair, endogenous vs. radiation-induced oxidative damage, adaptive responses, bystander effects, genomic instability and genetic susceptibility. The research is conducted at all levels of biological organization from molecular to organism. Detailed information is available on this Website on the individual projects funded, abstracts of past research, publications that have resulted to date from this research and past and future directions of the Program. To ensure that the data are carefully and appropriately evaluated, the Program is also funding projects on mathematical modeling. These projects help identify research needs and integrate the basic data into useful models of radiation cancer risks. In the future, the data from the DOE Low Dose Radiation Research Program will support molecular and genetic epidemiology, generate biologically-based risk models and help define the role that individual genetic susceptibility play in radiation-induced cancer risk. Such research will help insure that the standards are adequate and appropriate.

The Low Dose Radiation Research Program Update

April 2007

The Department of Energy’s Low Dose Radiation Research Program supports competitive peer-reviewed research aimed at informing the development of future national radiation risk policy for the public and the workplace. Since its beginning in 1999, the focus of research has been to study cellular and molecular responses to doses of x- or gamma- radiation that are at or near current workplace exposure limits; in general, for total radiation doses that are less than 0.1 Sievert (10 rem).

During the past year, the Low Dose Program supported projects have continued to expand current understanding of normal tissue responses to low doses of radiation. As of March 2007, there were at least 400 peer-reviewed publications coming from the Low Dose Program projects, 52 of which were published in the last year.

Solid epidemiological data from populations receiving high doses at high dose rates (mainly the Japanese A-Bomb survivor Life Span Study) have shown that ionizing radiation increases rates of cancer in human populations, at a level of roughly 5 or 6% per 1 Sv (or 6% /100 rem). However, traditional epidemiology has never been able to demonstrate significantly higher cancer risks in humans exposed to lower doses (below 0.1 Sv or 10 rem), or to chronic low dose rate exposures at somewhat higher total doses. Therefore, mathematical biophysical models were needed to develop health risk estimates for low doses of radiation.

In order to test the biophysical risk estimate models, animal life span studies were conducted during the 1960’s to 1990’s, measuring cancer incidence and cancer mortality in irradiated mice and dogs. As in human epidemiology, significantly higher cancer rates were not seen at the lowest doses, but only at the high dose exposures. Biological experiments were also undertaken using mammalian cell culture systems, in order to better understand the action of ionizing radiation at the molecular and cellular level.

Until recently, these biophysical models of radiation action have assumed independent action of ionization events in cells and tissues. The models assume that the single cell is the unit of function. The models also assume that every ionization event increases the probability of DNA breaks. Together, these physical/biological assumptions supported linear, no-threshold models of radiation risk and cancer. Historically, measurements of initial radiation damage such as cell death, chromosome aberrations, or micronuclei formation in cellular systems showed a fairly linear response with dose, but these experiments seldom encompassed doses lower than 0.5 Sv (50 rem).

New research from DOE’s Low Dose Program directly challenges the old fundamental assumptions. The new findings provide compelling evidence that ionization events in cells and tissues are not completely independent and that tissues have surveillance mechanisms that dramatically affect the development of cancer and the behavior of cancer cells. The research is establishing the tremendous importance of studying a tissue’s biological response to an exposure, rather than studying just the initial events within an individual cell.

A specific example of the new research is recent studies that highlight crosstalk between irradiated cells and nearby non-irradiated cells. This crosstalk cannot be explained with the older biophysical paradigms, which assume that the single cell is the unit of function. These data also show that cells within a tissue are not independent of each other in a multi-cellular organism. Indeed, the signaling from non-irradiated cells can actually eliminate damaged cells from a tissue. These and other results are consistent with the conclusions of the recent French National Academy Report “Dose-effect relationships and estimation of the carcinogenic effects of low doses of ionizing radiation” (March 2005). The growing body of research from the Low Dose Program now provides a legitimate scientific basis for stimulating reconsideration of models used to set regulatory standards.

The Low Dose Program is supporting research to help in the development of new mechanistic models that would incorporate all aspects of radiation biology, from cellular and molecular actions within tissues, to the evolution of cancer as a multi-cellular disease. Ongoing research in the Low Dose Program and advances in systems biology hold promise in providing this modeling framework, which can facilitate moving new biological paradigms into the regulatory process.