Lack of Effect Modification between Estrogen Metabolism Genotypes and Combined Hormone Replacement Therapy in Postmenopausal Breast Cancer Risk

Abstract

IntroductionPostmenopausal use of combined hormone replacement therapy (CHRT) containing both estrogens and progestins has been associated with increased breast cancer risk (1, 2). There is also evidence that genetic variants in candidate estrogen metabolism genes influence the disposition of exogenous estrogen. The genes involved in the disposition of estrogen are well known, and include catechol-O -methyltransferase (COMT), the sulfotransferases SULT1A1 and SULT1E1, and members of the cytochrome P50 family including CYP1B1, CYP1A2, and CYP1A1. Functionally relevant genetic variants exist in each of these genes. However, it remains unclear whether these genes affect breast cancer risk (3-10), and there is even less information about whether these genes interact with relevant exposures to influence breast cancer etiology. Therefore, we evaluated whether there was evidence for modification of the effect of CHRT use by genes involved in the downstream metabolism of estrogens including COMT, CYP1A1, CYP1A2, CYP1B1, SULT1A1, and SULT1E1. Materials and MethodsThe Women's Insights and Shared Experiences (WISE) study is a population-based case-control study that consisted of an efficient sampling design using shared controls to compare both breast cancer cases and endometrial cancer cases (11,12). Incident breast cancer cases were identified through hospitals and the Pennsylvania State Cancer Registry, and frequency-matched controls were identified from the community using random-digit dialing. The source populations for this study were the three counties of Philadelphia (PA), Delaware (PA), and Camden (NJ). Potentially eligible cases were Caucasian women residing in these counties at the time of diagnosis who were ages 50 to 79 years old and were newly diagnosed with breast cancer between July 1, 1999 and June 30, 2002. Controls were selected from the same geographic regions as the cases, and were frequency-matched to the cases on age (in 5-year age groups) and calendar date of interview (within 3 months). The present analysis involved 677 breast cancer cases and 905 age-matched controls who met the abovementioned criteria. Genomic DNA was obtained from buccal swabs as previously described. Genetic variants in COMT, CYP1A1, CYP1A2, CYP1B1, SULT1A1, and SULT1E1 were assayed as previously described (13). Additional details of our study design, which included ascertainment of both breast and endometrial cancer cases and matched controls, have been previously reported (11)(12)(13)(14).Odds ratio (OR) estimates and 95% confidence intervals were calculated to evaluate the relationship between hormone metabolism genes and hormone use with breast cancer risk. Using multiple conditional logistic regression, we adjusted for (a) education (<high school, high school graduate, more than high school but not a college graduate, college graduate or higher); (b) body mass index during the participant's 40's; (c) number of full-term pregnancies (0, 1, 2, 3+); (d) years of menses; (e) menopause type (known natural, assumed natural at re...

Polymorphisms in Genes Involved in Sex Hormone Metabolism, Estrogen Plus Progestin Hormone Therapy Use, and Risk of Postmenopausal Breast Cancer

“…Consistent with this, we observed that the increased risk of breast cancer associated with years of E+P use was greater among women with at least one rare allele of the CYP1A1 Ile 462 Val and CYP1A1 Msp I polymorphisms. To date, only one other study has evaluated interactions between SNPs in genes involved in hormone metabolism and years of E+P use in the development of breast cancer (31). Rebbeck et al (31) observed no statistically significant modification of the effect of E+P use on breast cancer risk by any of the polymorphisms that they studied; they evaluated CYP1A1 Ile 462 Val but not CYP1A1 Msp I.…”

Clique-Finding for Heterogeneity and Multidimensionality in Biomarker Epidemiology Research: The CHAMBER Algorithm

“…Simulated data were generated for eight genes to reflect the empirical dataset described below [30], [31], [32] (Figure 2). Dataset D1 had no factors that confer risk of being a case vs. a control.…”

“…These simulated data were intended to reflect frequently encountered empirical allele and genotype frequencies, including unknown (missing) genotypes. Specifically, we generated these simulated data to reflect the data observed in the WISE study [30], [31], [32]. For each dataset, 500,000 individuals were generated to model a variety of genetic risk scenarios involving one or more genotypes conferring an enhanced risk of disease.…”

Polymorphisms in genes of respiratory control and sudden infant death syndrome

“…SULT1A1 catalyzes the sulfate conjugation of small phenols, such as neurotransmitters and steroid hormones, and rs1801030 defines the SULT1A1*3 allozyme with a p.M223V change (c.A667G) [26]. The *3 variant has a similar or lower intrinsic enzyme activity compared to both the *1 and *2 variant, depending on the substrate [27]. The enzyme activity with regard to serotonin, dopamine, or (nor) adrenaline has not been investigated yet, though one can assume a normal-activity allozyme that has no effect on the catabolism on the before-mentioned neurotransmitters [28].…”