Genetic Susceptibility, Predicting Risk and Preventing Cancer

Abstract

A polygenic approach to disease prevention has become a realistic goal that has arisen from the sequencing of the human genome. Some believe it will be possible to identify individuals as susceptible by their genotype and to prevent disease by targeting interventions to those at risk. However, doubts have been expressed about the magnitude of these genetic effects, and hence the potential to apply them either to individuals or to populations. Published data suggest that the familial aggregation of breast cancer not due to the known high penetrance genes is polygenic, which implies that the distribution of risk in the population is continuous. This model is likely to apply to other common cancers. The utility of a continuous distribution for identifying a high-risk group of the population for targeted preventive intervention depends on the spread of that risk distribution. For breast cancer, the data are compatible with a log-normal distribution of genetic risk in the population which is sufficiently wide to provide useful discrimination of high- and low-risk groups. Assuming all the susceptibility genes could be identified, the half of the population at highest risk would account for 88% of all cases. In contrast, if currently identified risk factors for breast cancer were used to stratify the population, the half of the population at highest risk would account for only 62% of all cases. These results suggest that in the future the construction and use of genetic risk profiles may provide significant improvements in the efficacy of population-based programmes of intervention for cancers and other diseases.