Women of African ancestry (AA) women are more likely than those with European ancestry (EA) to be diagnosed with breast cancer before age 45, and to have more aggressive tumors, characterized by high grade, with negative staining for estrogen and progesterone receptors and HER-2 (triple negative). They are also more likely to have basal-like breast tumors, an intrinsic breast cancer subtype with the poorest prognosis. The reasons for these disparities are unclear, and existing studies lack the statistical power to investigate risk factors for breast cancer subtypes among young women. In this Program Project, we will pool data and samples from the Carolina Breast Cancer Study (CBCS), the Black Women's Health Study (BWHS), the Women's Circle of Health Study (WCHS) and the Multi-ethnic Cohort (MEC) and continue to accrue cases for a final sample size of more than 5500 cases and 5500 controls. We will collect tissue blocks and classify cancers by their intrinsic subtypes, and investigate specific genetic, biologic and epidemiologic risk factors for subtypes in four highly interactive projects. The specific aims are to examine associations between age at diagnosis and breast cancer subtypes and 1) genetic loci identified in recent GWAS findings, using fine-mapping to identify potential causal alleles; 2) pregnancy history and lactation, and potential modification by genetic variants in related pathways; 3) body size, early life and adult physical activity, and gene/environment interactions; and 4) risk factors that may have been adaptive in Africa to endemic infectious disease (robust immune response) and intense sunlight (high skin pigmentation), but that in western society may result in hyper-inflammatory milieu and vitamin D deficiency, which may be related to early, aggressive breast cancer. Interactive aims will investigate relationships between subtypes and genetic and biologic factors, as well as epidemiologic characteristics. Cores that support all of the projects include the 1) Administrative Core; 2) Data Collection Core; 3) Biospecimen Core; and 4) Biostatistics and Data Management Core. By pooling our data, specimens, and importantly, expertise to investigate these synergist hypotheses, we will elucidate much of the etiology of aggressive, early onset breast cancers in AA women.