Genetic Studies of Mammographic Density Dense breast tissue is one of the strongest known risks for breast cancer and is measured as percent mammographic density (PMD). Differences in PMD reflect differences in breast tissue composition. Given that the heritability of PMD is high (63%) as estimated from twin studies, the contributors to PMD are hypothesized to be amenable to genetic mapping approaches. The major genetic determinants of radiographically dense breast tissue will be identified by quantitative trait linkage analysis with the long-term goal of identifying susceptibility genes for breast cancer. The proposal builds on previous studies demonstrating the high heritability of PMD and on candidate gene associations.
In Aim 1, critical resources for the proposed genetic studies will be recruited from a collection of dizygotic twins used in previous studies and a breast cancer case-based collection of over 1,800 sibpairs, recruited through the Collaborative Breast Cancer Family Registries funded by the National Cancer Institute.
In Aim 2, genome-wide linkage studies will be carried out to identify major loci for PMD, followed by Aim 3 with refined mapping using both linkage and association analyses. Genes within associated intervals defined by markers and/or haplotypes will be pursued with the aim of additional refinement, and understanding of the expression and functional consequences of the associated haplotypes. Further, a series of genes implicated by their active role in breast tissue biology through involvement with estrogen metabolism will be directly tested for association with PMD in Aim 4 using the large combined collection. A phased approach will begin with the selection of markers that tag common haplotypes, as identified by the HapMap Consortium. Finally, in Aim 5, the gene variants associated with PMD from Aims 3 and 4 will be tested for association with breast cancer. The long term objectives are to gain insight into breast biology and to assist in the prediction and diagnosis of breast cancer, and ultimately to provide for prevention strategies and more effective treatments.
| Linton, Linda; Martin, Lisa J; Li, Qing et al. (2013) Mammographic density and breast cancer: a comparison of related and unrelated controls in the Breast Cancer Family Registry. Breast Cancer Res 15:R43 |
| Greenwood, Celia M T; Paterson, Andrew D; Linton, Linda et al. (2011) A genome-wide linkage study of mammographic density, a risk factor for breast cancer. Breast Cancer Res 13:R132 |
