Abstract Background:Breast cancer risk assessment professionals employ models to estimate individual probabilities of developing breast cancer. The Gail, Claus and BRCAPro models integrate personal, reproductive and family history variables to generate absolute risk estimates. A number of common DNA variants (single nucleotide polymorphisms, SNPs) are associated with modest elevations (relative risk < 2) of breast cancer risk. We investigated the correlation between genotype at 18 published risk SNPs and model-derived breast cancer risk estimates.Methods:Subjects were 475 unaffected, BRCA mutation-negative women who were evaluated for a family history of breast or ovarian cancer. At the time of testing, subjects provided information that was used to estimate absolute breast cancer risk by Gail, Claus, and BRCAPro models. Subjects were genotyped by Sequenom iPLEX MassArray (Sequenom, Inc., San Diego, CA) at loci reported to be associated with elevations in breast cancer risk (1p11.2, 2q35, 5p12, 6q22.33, 8q24, CASP8, COX11, FGFR2, LSP1, MAP3K1, RAD51L1, SLC4A7, TNRC9). Kruskal-Wallis and Spearman correlation tests were used to compare risk estimates for individuals by genotype and number of risk alleles.Results:The median age at sample donation was 46 years (range 24-83). Most subjects (94.9%) were white, and 65.5% were of Ashkenazi Jewish (AJ) ancestry. Median breast cancer risk scores risk estimates were significantly lower from BRCAPro (5 yr: 1.1%, lifetime (LT): 11.6%) than those derived from Gail (5 yr: 1.8%, LT: 18.5%) or Claus (5 yr: 1.5%, LT: 11.8%) models. No significant differences (p>0.05) in distribution of estimated breast cancer risk scores were found between women carrying 0, 1, or 2 risk alleles at any locus except 6q22.33, where AJ women homozygous for the risk allele rs2180341 were noted to have higher LT Claus (p=0.001) and BRCAPro (p=0.01) estimates. When comparing subjects with no risk alleles to those with 1-2 risk alleles for each SNP, no significant differences in distribution of estimated risk were noted at any loci, including 6q22.33. There was no significant correlation between the total number of risk alleles carried by a subject and her estimated lifetime Gail (ρ=-0.052, P=0.27), Claus (ρ=0.051, P=0.32), or BRCAPro (ρ=0.024, P=0.60) risk.Conclusions:In this analysis, risk allele genotype did not correlate with absolute breast cancer risk estimated by standard models. This suggests that the contribution to risk of genotype at these SNPs is insufficient to impact the modeled estimate. Further studies are necessary to evaluate whether incorporation of genotypic information can improve the calibration or discriminatory accuracy of existing models. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 901.