Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 × 10(-5)) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)(2)). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.

Original publication

DOI

10.1093/aje/kwu214

Type

Journal article

Journal

Am J Epidemiol

Publication Date

15/11/2014

Volume

180

Pages

1018 - 1027

Keywords

additive interactions, breast cancer, genome-wide association studies, single-nucleotide polymorphisms, Alleles, Australia, Biomarkers, Tumor, Body Mass Index, Breast Neoplasms, Case-Control Studies, Cohort Studies, DNA-Binding Proteins, Europe, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Odds Ratio, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Rad51 Recombinase, Risk Assessment, Risk Factors, United States