DESCRIPTION (provided by applicant): Higher mammographic density is an independent risk factor for breast cancer and the magnitude of risk associated with mammographic density is greater than that associated with almost all other known risk factors for breast cancer. This application proposes to continue work in "Sex Steroids and Mammographic Density in the Postmenopause", a study of the effects of endogenous and exogenous sex steroids on mammographic percent-density. This study is an outgrowth of the Postmenopausal Estrogen/Progestin Interventions (PEPI) trial, which randomly assigned postmenopausal women to placebo, estrogen-only, or one of three combination estrogen/progestin treatments. To date, the principal findings of the "Sex Steroids and Mammographic Density Study" are: 1) Exogenous estrogen-only treatment did not affect mean mammographic density but significant increases in mammographic density did occur in 3 groups assigned to estrogen/progestin treatments; 2) In the three estrogen/progestin groups, but not in the estrogen-only group, the degree of increase in serum estrone level on-treatment predicted the amount of increase in mammographic density; and 3) Endogenous (pre-treatment) serum levels of estrone, estradiol, progesterone, and sex hormone binding globulin were positively associated with baseline mammographic density. Based on these findings, we propose to continue work in this study to gain a further understanding of variation in mammographic density, specifically: 1) What other factors are associated with baseline (pre-treatment) mammographic density? and 2) What additional factors predict increases in mammographic density during treatment? We hypothesize that hormones (in addition to those already studied), genetic polymorphisms in sex steroid biosynthetic/metabolic pathways, and genetic polymorphisms in sex steroid receptors will be related to baseline mammographic density and/or mammographic density response to treatment with hormone therapy. The proposed continuation project will last 4 years and will take place at UCLA and USC. Using stored samples, we will measure baseline and 12-month levels of prolactin and progestins. We will also extract DNA from stored samples to assess selected genetic polymorphisms. The mammographic density outcome data and all relevant covariates have already been measured during our prior work. We will quantify the relations between the hormone and genetic exposures measured in this project and mammographic density (at baseline as well as change in density between baseline and 12 months).
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