TY - JOUR
T1 - Combined associations of genetic and environmental risk factors
T2 - Implications for prevention of breast cancer
AU - Garcia-Closas, Montserrat
AU - Gunsoy, Necdet Burak
AU - Chatterjee, Nilanjan
N1 - Funding Information:
MGC is funded by the Institute of Cancer Research and Breakthrough Breast Cancer, UK. NBG is funded by the Institute of Cancer Research, UK. NC is funded by Intramural Funds of the National Cancer Institute, National Institutes of Health.
PY - 2014/11/1
Y1 - 2014/11/1
N2 - 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.
AB - 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.
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U2 - 10.1093/jnci/dju305
DO - 10.1093/jnci/dju305
M3 - Review article
C2 - 25392194
AN - SCOPUS:84984985158
SN - 0027-8874
VL - 106
JO - Journal of the National Cancer Institute
JF - Journal of the National Cancer Institute
IS - 11
M1 - dju305
ER -