Mammographic density is one of the strongest risk factors for breast cancer. High mammographic density is common, and has been estimated to account for up to one-third of breast cancers diagnosed in the U.S. Most of the variation in mammographic density is explained by hereditary factors that remain largely unknown. Our primary goal is to identify novel density genes by conducting a genome-wide association study (GWAS) in ~30,000 women participating in the Kaiser Permanente Northern California (KPNC) Research Program on Genes, Environment and Health (RPGEH), who are e40 years of age and have had at least one screening mammogram at KPNC. The RPGEH is an ideal setting for this study because of the availability of genome- wide data for over 650K SNPs, centrally stored digitized film mammograms, and extensive epidemiologic and medical data.
The specific aims are to: (1) Characterize all eligible RPGEH women with regard to mammographic density and factors known or suspected to be associated with density;(2) Conduct a GWAS in ~30,000 RPGEH women to identify novel density genes with excellent power at a stringent genome-wide significance threshold of 1 10-8, replicate significant findings in an external population of 4,877 women with GWAS data in the Markers of Density (MODE) consortium, and evaluate potential modification of density alleles by non-genetic factors;and (3) Investigate the genetic basis for the association of mammographic density with breast cancer risk using GWAS data for over 15,000 breast cancer cases and 18,000 controls from the NCI U19 international consortium. This cost-efficient study will be several-fold larger than previous studies of mammographic density and will have excellent power to identify novel density genes. The identification of genes underlying mammographic density will help improve our understanding of the biology of breast tissue composition and may reveal new targets for the prevention and treatment of breast cancer.
High mammographic breast density accounts for up to one third of the breast cancers diagnosed in the U.S. and are highly heritable. This project addresses the genetic basis of mammographic breast density. The identification of novel breast density genes may reveal new targets for prevention and treatment, and ultimately help reduce the public health burden of breast cancer.
| Jeffers, Abra M; Sieh, Weiva; Lipson, Jafi A et al. (2017) Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADS. Radiology 282:348-355 |
| Alexeeff, Stacey E; Odo, Nnaemeka U; Lipson, Jafi A et al. (2017) Age at Menarche and Late Adolescent Adiposity Associated with Mammographic Density on Processed Digital Mammograms in 24,840 Women. Cancer Epidemiol Biomarkers Prev 26:1450-1458 |
| Habel, Laurel A; Lipson, Jafi A; Achacoso, Ninah et al. (2016) Case-control study of mammographic density and breast cancer risk using processed digital mammograms. Breast Cancer Res 18:53 |
