Abstract 60: Combined effects of low-penetrance variants on breast cancer risk: Results from the Seoul Breast Cancer Study.

Abstract

Background: Although several low-penetrance loci associated with breast cancer risk were identified and confirmed, knowledge of the effect of multiple risk alleles is limited especially in Asian women. Therefore we evaluated the association between the polygenic risk scores and breast cancer risk in Korean women using the most recent list of breast cancer susceptibility loci.

Methods: We analyzed 51 single-nucleotide polymorphisms (SNPs) located in 34 loci in 1,774 cases and age-frequency matched 1,774 control subjects participating in Seoul Breast Case-Control Study. The fourteen independent SNPs associated with breast cancer risk were selected based on the results of single SNP analysis. The genetic risk score (GRS) were calculated using simple count method and weighted method. Tests of association were conducted using the logistic regression for quintiles of each GRS with or without adjustment. The c-statistic was estimated to evaluate the contribution of GRS to risk prediction model including non-genetic factors (age, family history of breast cancer, education, BMI, menopausal status, age at menarche, age at first full-term pregnancy, and number of children).

Results: Fourteen SNPs (rs13393577, rs4973768, rs7716600, rs1092913, rs889312, rs9485372, rs2046210, rs1562430, rs704010, rs10736303, rs7107217, rs10771399, rs3803662, and rs4784227), each of which reflected a genetically independent locus, were found to be associated with breast cancer risk. A highly significant trend was observed between the GRS and the risk of breast cancer. The adjusted odds ratios for women in the highest quintile of count GRS or weighted GRS vs. those in the lowest were 2.64 (95% confidence interval (95% CI), 2.09- 3.35; Ptrend=9.3E-19) and 2.76 (95% CI, 2.18- 3.50; Ptrend=5.9E-21), respectively. The c-statistic for model including the GRS in additional to the conventional risk factors was 0.6389 (95% CI, 0.620-0.658) vs. 0.6041 (95% CI, 0.585-0.623) with the conventional risk factors only.

Conclusions: Supporting the polygenic inheritance model of breast cancer, our study showed that GRS based on low-penetrance SNPs adds very modest improvement to risk prediction models.

Citation Format: Hyuna Sung, Ji-Yeob Choi, Sue K. Park, Wonshik Han, Keun-Young Yoo, Sei-Hyun Ahn, Dong-Young Noh, Daehee Kang. Combined effects of low-penetrance variants on breast cancer risk: Results from the Seoul Breast Cancer Study. [abstract]. In: Proceedings of the AACR Special Conference on Post-GWAS Horizons in Molecular Epidemiology: Digging Deeper into the Environment; 2012 Nov 11-14; Hollywood, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2012;21(11 Suppl):Abstract nr 60.