In the United States, breast cancer is the most frequently diagnosed non-skin cancer in women, and one in five women who are diagnosed develop breast cancer before age 50. Germline genetic variation is a known risk factor for breast cancer risk, and a suspected risk factor for breast cancer mortality, but previous investigations have not comprehensively identified all of the genetic variation that is expected to be associated with breast cancer. One possible explanation for this gap in knowledge is the only relatively recent ability to investigate the effect of rare germline genetic variation, which up until recently has been too expensive and technically challenging to measure in the a large number of participants that are necessary for genetic epidemiologic studies, and the methodological challenges of identifying rare variants. This thesis uses three complementary methods (single marker regression analysis, SKAT-O gene-based tests, and candidate gene) to identify individual risk loci and three additional complementary methods (Kriging whole genome prediction, polygenic risk scores, and whole genome heritability estimates) to predict breast cancer risk and breast cancer mortality using a population of women who were diagnosed with breast cancer before the age of 50. Suggestively associated risk loci were examined for evidence of replication using an independent sample. For breast cancer risk, the identification analyses find three genes in which variation is associated with risk of breast cancer: FGFR2 (discovery p=2.18e-5; replication p<1e-30), NEK10 (discovery p=1.20e-3; replication p<1e-30), and MKL1 (discovery p=2.62e-4; replication p




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