P1-09-04: A Genetic Predictor for Breast Cancer Risk in a Japanese Population.
Authors: Sueta A , Ito H , Iwata H , Hosono S , Watanabe M , Iwase H , Tajima K , Tanaka H , Matsuo K 
Published: June 2012

Objective Genome-wide association studies (GWASs) have identified genetic variants associated with breast cancer. Most GWASs to data were conducted in women with European background and the extent to which these variants contribute as predictors of breast cancer among Japanese population is unknown.

Methods We analyzed 24 genetic variants that have been identified in previous GWASs and conducted a case-control study with 697 cases and age- and menopausal status- matched 1394 controls in the framework of the Hospital-based Epidemiologic Study at Aichi Cancer Center (HERPACC). All subjects were asked to provide information on lifestyle factors and blood samples for genetic studies. We fit conditional regression models with genetic variants and conventional risk factors including age, age at menarche, menopausal status, current body-mass-index, age at first live birth, regular exercise, family history of breast cancer, and referral pattern to our hospital. In addition, we created a polygenetic risk score, using the single nucleotide polymorphisms (SNPs) with statistically significant association with the breast cancer risk to measure the cumulative effect of multiple genetic risk variants. Furthermore, we evaluated the prediction model that included conventional risk factors by comparing with and without the genetic risk score, using c statistic.

Results Eleven SNPs (FGFR2-rs2981579, rs2981578, rs1219648, rs2420946, rs2981582, TOX3/TNRC9-rs8051542, rs3803662, LOC643714-rs4784227, C6orf97-rs2046210, 8q24-rs13281615, SLC4A7-rs4973768) revealed significant associations with breast cancer risk (each P &lt; 0.05 in either per allele, dominant, or recessive model). A dose-dependent association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the alleles in 7 selected variants; rs2981579, rs3803662, rs2046210, rs13281615, rs4973768, rs3817198 and rs10931936. Compared to women with scores of 3 or less, odds ratios (ORs) for women with scores of 4–5, 6–7, 8–9 and 10 or more were 1.33 (95% confidence interval, 1.00 - 1.80), 1.71 (1.26 - 2.30), 3.01 (1.97 - 4.58) and 8.69 (2.74 - 27.5), respectively (Ptrend &lt; 0.001). The ORs for premenopausal women with the corresponding risk scores were 1.71 (1.12 - 2.63), 1.79 (1.15 - 2.78), 3.70 (1.98 - 6.93), and 14.0 (3.30–59.5), respectively, and those for postmenopausal women with the corresponding risk scores were 1.09 (0.72 - 1.66), 1.71 (1.12 - 2.61), 2.60 (1.44 - 4.71), 3.75 (0.57 - 24.4), respectively, compared to those with scores of 3 or less (each Ptrend &lt; 0.001). The c statistic for a model including the genetic risk score in addition to the conventional risk factors was 0.633, whereas 0.602 without it (P &lt; 0.001). Population-attributable fraction of the risk score was 33.8%.

Conclusion we identified a genetic predictor of breast cancer in a Japanese population. A risk model including genetic risk score may be useful to distinguish women at high-risk of breast cancer from those at low-risk, particularly in the context of targeted prevention.

Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P1-09-04.