Combined associations of genetic and environmental risk factors: implications for prevention of breast cancer

Abstract

Genome-wide association studies (GWAS) have identified hundreds of genetic susceptibility loci for cancers and other complex diseases. However, the public health and clinical relevance of these discoveries is unclear. Evaluating the combined associations of genetic and environmental risk factors, particularly those that can be modified, will be critical in assessing the utility of genetic information for risk stratified prevention. In this commentary, using breast cancer as a model, we show that genetic information in combination with other risk factors can provide levels of risk stratification that could be useful for individual decision-making or population-based prevention programs. Our projections are theoretical and rely on a number of assumptions, including multiplicative models for the combined associations of the different risk factors, which need confirmation. Thus, analyses of epidemiological studies with high-quality risk factor information, as well as prevention trials, are needed to empirically assess the impact of genetics in risk stratified prevention.

Figure 1.

Partial Receiver Operating Curves (ROC) showing the percentage of cases of breast cancer expected to occur in groups of the population at highest predicted risk (A, C), and graphs for the percentage of the population crossing breast cancer relative risk (RR) thresholds (compared with the average risk in the population) (B, D). Estimates are for a UK population of women aged 50 years, for eight risk prediction models, including different sets of risk factors and two polygenic risk scores (PRSs): the 76–single nucleotide polymorphism (SNP) PRS based on currently known SNPs explaining 15% of the familial risk (A, B) and an improved PRS explaining 30% of the familial risk (C, D). PRS = polygenic risk score; Qx = questionnaire; SNP = single nucleotide polymorphism.