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Genetics of Mammographic Density

Grant number: X01HG005141
PI Name: Ziv E
Title: Genetics of Mammographic Density


Background: Mammographic breast density is a strong predictor of breast cancer risk. Among women in the highest quartile of breast density, the risk of breast cancer is elevated approximately 4-fold compared with women in the lowest quartile. Breast density is also a highly heritable trait; twin studies have estimated that ~60% of the variation in breast density is explained by genetic factors. First degree relatives of women with the highest breast density have a higher risk of breast cancer than the first degree relatives of women with the lowest breast density. These findings suggest that the genes that underlie breast density should also predict breast cancer risk and that breast density is a useful intermediate quantitative trait for finding breast cancer susceptibility genes. Whole genome association studies are a potentially powerful approach to discovering genetic variants that underlie complex traits, and recent advances in technology have made these studies feasible.

Objective: The goals of this project are to identify the genes and genetic variants that determine variation in breast density and to evaluate how those genetic variants affect breast tissue, specifically breast stromal tissue that may underlie the association between breast density and breast cancer risk. Methods: (1) We will use whole genome association technology (the Illumina Infinium 370K array) to discover specific polymorphisms and/or haplotypes that differ between 300 women from the high density group and 300 women from low density group in the SFMR. We will then replicate the top 1% of discoveries from the whole genome association in an additional 300 women with high and low breast density. (2) Using the candidate polymorphisms that are confirmed in phase 2, we will perform fine mapping to discover the causal genes and specific variants in these genes. Fine mapping will be performed in the same samples used for specific aim 1.

Summary: Our approach will be made considerably more efficient by an existing collection of over 5000 blood samples collected on women in the SFMR who have had quantitative breast density measured from mammograms. In addition, our approach will be considerably enhanced by linkage to a large ongoing effort at understanding the basic biology of breast density (P01, PI Tlsty.) Follow up studies will include: (1) testing the associations we identify with breast density with histological and molecular factors identified by Dr. Tlsty and colleagues to be associated with high breast density and with activated stroma in benign breast biopsy tissue. (2) testing the SNPs we identify in specific aims 1 and 2 with breast cancer risk.