Chapter 4 describes the evaluations of the associations between loci linked in genome-wide association studies to breast cancer risk, and mammographic density parameters, by using recently developed PRS. Chapter 3 details the assessment heterogeneity in the relationships between mammographic density parameters and breast cancer risk, according to tumor characteristics. In Chapter 2 estimates of the effects of mammographic density parameters on the risk of breast cancer are computed, using causal inference methods for observational studies. Detailed questionnaire and clinical information, as well as measured breast density from screening mammography films, were collected.

The objectives of this work were to (1) determine the association between non-dense area and breast cancer, as well as confirming the association between dense area and breast cancer, (2) assess the discriminating power captured by the non-dense area parameter on models forecasting breast cancer, (3) estimate breast cancer risk for mammographic density parameters by breast cancer tumor characteristics, and (4) evaluate the relationship between polygenic risk scores (PRS) generated developed to predict genetic risk of breast cancer with mammographic density parameters.Ī population-based case-control study conducted in Vancouver, BC, was used. In addition, not much is known about how the variation in breast cancer related single nucleotide polymorphisms (SNPs) is associated with mammographic density, but given its high heritability, it is possible common genetic determinants could affect both mammographic density and breast cancer. Furthermore, even though the associations between breast cancer and known risk factors differ by tumor characteristics, this has not been clearly demonstrated for mammographic density. The association between mammographic density and breast cancer risk is well known, however, the role of absolute non-dense area remains unclear.

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