Association studies have been widely used to search for common low-penetrance susceptibility alleles to breast cancer in general. However, breast cancer is a heterogeneous disease and it has been suggested that it may be possible to identify additional susceptibility alleles by restricting analyses to particular subtypes. We used data on 710 single nucleotide polymorphisms (SNP) in 120 candidate genes from a large candidate gene association study of up to 4,470 cases and 4,560 controls to compare the results of analyses of "overall" breast cancer with subgroup analyses based on the major clinicopathologic characteristics of breast cancer (stage, grade, morphology, and hormone receptor status). No SNP was highly significant in overall effects analysis. Subgroup analysis resulted in substantial reordering of ranks of SNPs, as assessed by the magnitude of the test statistics, and some associations that were not significant for an overall effect were detected in subgroups at a nominal 5% level adjusted for multiple testing. The most significant association of CCND1 SNP rs3212879 with estrogen receptor-negative tumor types (P = 0.001) did not reach genome-wide significance levels. These results show that it may be possible to detect associations using subgroup analysis that are missed in overall effects analysis. If the associations we found can be replicated in independent studies, they may provide important insights into disease mechanisms in breast cancer.