CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer.

Candidate gene studies have reported CYP19A1 variants to be associated with endometrial cancer and with estradiol (E2) concentrations. We analyzed 2937 single nucleotide polymorphisms (SNPs) in 6608 endometrial cancer cases and 37 925 controls and report the first genome wide-significant association between endometrial cancer and a CYP19A1 SNP (rs727479 in intron 2, P=4.8×10(-11)). SNP rs727479 was also among those most strongly associated with circulating E2 concentrations in 2767 post-menopausal controls (P=7.4×10(-8)). The observed endometrial cancer odds ratio per rs727479 A-allele (1.15, CI=1.11-1.21) is compatible with that predicted by the observed effect on E2 concentrations (1.09, CI=1.03-1.21), consistent with the hypothesis that endometrial cancer risk is driven by E2. From 28 candidate-causal SNPs, 12 co-located with three putative gene-regulatory elements and their risk alleles associated with higher CYP19A1 expression in bioinformatical analyses. For both phenotypes, the associations with rs727479 were stronger among women with a higher BMI (Pinteraction=0.034 and 0.066 respectively), suggesting a biologically plausible gene-environment interaction.

Genome-wide association study of circulating estradiol, testosterone, and sex hormone-binding globulin in postmenopausal women.

Genome-wide association studies (GWAS) have successfully identified common genetic variants that contribute to breast cancer risk. Discovering additional variants has become difficult, as power to detect variants of weaker effect with present sample sizes is limited. An alternative approach is to look for variants associated with quantitative traits that in turn affect disease risk. As exposure to high circulating estradiol and testosterone, and low sex hormone-binding globulin (SHBG) levels is implicated in breast cancer etiology, we conducted GWAS analyses of plasma estradiol, testosterone, and SHBG to identify new susceptibility alleles. Cancer Genetic Markers of Susceptibility (CGEMS) data from the Nurses' Health Study (NHS), and Sisters in Breast Cancer Screening data were used to carry out primary meta-analyses among ~1600 postmenopausal women who were not taking postmenopausal hormones at blood draw. We observed a genome-wide significant association between SHBG levels and rs727428 (joint ß = -0.126; joint P = 2.09 × 10(-16)), downstream of the SHBG gene. No genome-wide significant associations were observed with estradiol or testosterone levels. Among variants that were suggestively associated with estradiol (P<10(-5)), several were located at the CYP19A1 gene locus. Overall results were similar in secondary meta-analyses that included ~900 NHS current postmenopausal hormone users. No variant associated with estradiol, testosterone, or SHBG at P<10(-5) was associated with postmenopausal breast cancer risk among CGEMS participants. Our results suggest that the small magnitude of difference in hormone levels associated with common genetic variants is likely insufficient to detectably contribute to breast cancer risk.

Familial correlations in postmenopausal serum concentrations of sex steroid hormones and other mitogens: a twins and sisters study.

BACKGROUND: Serum concentrations of some hormones are risk factors for certain cancers, but little is known about their familial associations especially for females. METHODS: We measured serum concentrations of estradiol (E(2)), testosterone (T), SHBG, prolactin, and IGF-I for 645 Australian female postmenopausal twins and their sisters [182 monozygotic (MZ) and 107 dizygotic (DZ) pairs and 67 nontwin sisters] using well-established immunoassays. After suitable transformation and adjusting for age, body mass index (BMI), and time since menopause, familial correlations and proportions of variance attributed to genetic (h(2)) and nongenetic factors common to sisterships (c(2)) were estimated under the classic twin multivariate normal model using FISHER. RESULTS: For all serum concentrations except prolactin, MZ, DZ, and sister pairs were correlated (P < 0.001). MZ correlations were in the range 0.5-0.7, and for all serum concentrations, there were no differences between DZ and sister correlations. MZ correlations were greater than DZ and sister correlations for log SHBG (P = 0.0001), IGF-I (P = 0.0002), and square-root T (P = 0.007) but not log E(2) (P = 0.3), and the respective h(2) estimates were 0.56 (SE = 0.14), 0.53 (0.17), 0.39 (0.14), and 0.14 (0.16). For log E(2) and square-root T, c(2) estimates were 0.39 (0.14) and 0.22 (0.12). CONCLUSION: There are strong familial correlations in postmenopausal SHBG, IGF-I, and to a lesser extent T, which are consistent with a genetic etiology. For E(2), and to a lesser extent T, correlations are consistent with substantial nongenetic familial factors. The latter might include maternal effects.

Effect of delays in processing blood samples on measured endogenous plasma sex hormone levels in women.

Time spent in transit may affect the concentration of various constituents of collected blood samples and, consequently, results of sex hormone assays. Whole blood was collected from 46 women, and one third was processed immediately, one third was stored at ambient conditions (22 degrees C) for 1 day, and one third was stored for 2 days. Estradiol concentration increased by 7.1% [95% confidence interval (95% CI), 3.2-11.3%] after a delay in processing of 1 day and by 5.6% (95% CI, 0.2-11.4%) after a delay in processing of 2 days; the change was most apparent at lower than median concentrations. Progesterone concentrations showed no substantial change. Testosterone concentrations changed by 23.9% (95% CI, 17.8-30.3%) after a delay of 1 day but little thereafter. The sex hormone-binding globulin concentration decreased by 6.6% (95% CI, 4.6-8.6%) and 10.9% (95% CI, 8.1-13.6%), follicle-stimulating hormone increased by 7.4% (95% CI, 4.2-10.7%) and 13.9% (95% CI, 8.7-19.3%), and luteinizing hormone increased by 4.9% (95% CI, 1.3-8.5%) and 6.7% (95% CI, 2.2-11.5%) after a delay in processing of 1 and 2 days. Increases in calculated values for biologically available levels of estradiol and testosterone were greater than the increases seen in measured total hormone concentrations. Similar changes are likely when samples are delayed in transit, and evidence of etiology may be obscured unless study designs or analyses take into account processing delays.

Phytoestrogen exposure is associated with circulating sex hormone levels in postmenopausal women and interact with ESR1 and NR1I2 gene variants.

In this large cross-sectional study, we investigated the relationship between phytoestrogen exposure and circulating sex hormones and sex hormone-binding globulin (SHBG) levels in 1988 healthy postmenopausal women and their interactions with polymorphisms in genes involved in estrogen signaling. Plasma estradiol, testosterone, androstenedione, estrone, and SHBG were measured. Urinary levels of five isoflavones (daidzein, genistein, glycitein, O-desmethylangolensin, and equol) and two lignans (enterodiol and enterolactone) were measured and used as biomarkers for dietary intakes. Eighteen polymorphisms in ESR1, ESR2, and NR1I2 genes were genotyped. Results showed that lignans were positively associated with plasma SHBG levels (eta(p)(2) = 1.2%; P < 0.001) and negatively associated with plasma testosterone (eta(p)(2) = 0.2%; P = 0.042). Equol was negatively associated with plasma estradiol levels (eta(p)(2) = 0.3%; P = 0.028), whereas O-desmethylangolensin was positively associated with plasma estradiol level (eta(p)(2) = 0.3%; P = 0.010). There were significant phytoestrogen interactions with polymorphisms in ESR1 and NR1I2 genes in affecting estrone levels. We conclude that phytoestrogens modulate sex hormone and SHBG levels in postmenopausal women and interact with gene variants involved in estrogen signaling. Such phytoestrogen-gene interactions may explain the conflicting literature on the hormonal effects of phytoestrogens.

Associations among mammographic density, circulating sex hormones, and polymorphisms in sex hormone metabolism genes in postmenopausal women.

Mammographic density and serum sex hormone levels are important risk factors for breast cancer, but their associations with one another are unclear. We studied these phenotypes, together with single nucleotide polymorphisms (SNP) in genes related to sex hormone metabolism, in a cross-sectional study of 1,413 postmenopausal women from the European Prospective Investigation into Cancer and Nutrition-Norfolk. All women were >1 year postmenopausal and had not taken hormone replacement therapy for >3 months before sampling. Serum levels of 7 sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG), androstenedione, 17-OH-progesterone, estrone, and estrone sulfate] and 15 SNPs in the CYP17, CYP19, EDH17B2, SHBG, COMT, and CYP1B1 genes were studied. Mammograms nearest in time to the blood sampling were identified through the national breast screening program and visually assessed by three radiologists using the Boyd six-category and Wolfe four-category scales. We found a weak positive association between mammographic density and SHBG levels (P = 0.09) but no association with any other hormones. None of the SNPs, including those shown previously to be associated with estradiol or SHBG, showed significant associations with density. We conclude that mammographic density is largely independent of postmenopausal steroid hormone levels, indicating that these risk factors have, to a large extent, an independent etiology and suggesting that they may be independent predictors of breast cancer risk.

Polymorphisms in the CYP19 gene may affect the positive correlations between serum and urine phytoestrogen metabolites and plasma androgen concentrations in men.

Phytoestrogens have been hypothesized to protect against prostate cancer via modulation of circulating androgen concentrations. We conducted a cross-sectional study of 267 men in the Norfolk arm of the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort with 2 aims: first, to investigate the association between phytoestrogen exposure (measured from diet, urine, and serum) and plasma concentrations of sex hormone-binding globulin (SHBG), androstanediol glucuronide, testosterone and Free Androgen Index (FAI); and second, whether the association may be modified by polymorphisms in CYP19 and SHBG genes. Dietary daidzein and genistein intakes were obtained from food diaries and computed using an in-house food composition database. Urinary and serum concentrations of 3 isoflavones (daidzein, genistein, glycitein), 2 daidzein metabolites O-desmethylangolensin (O-DMA) and 2 lignan metabolites (enterodiol and enterolactone) were measured using mass spectrometry. There was no association between dietary, urinary, and serum phytoestrogens and plasma SHBG concentrations. Enterolactone was positively associated with plasma androstanediol glucuronide concentrations (urinary enterolactone: r = 0.127, P = 0.043; serum enterolactone: r = 0.172, P = 0.006) and FAI (urinary enterolactone: r = 0.115, P = 0.067; serum enterolactone: r = 0.158, P = 0.011). Both urinary and serum equol were associated with plasma testosterone (urinary equol: r = 0.332, P = 0.013; serum equol: r = 0.318, P = 0.018) and FAI (urinary equol: r = 0.297, P = 0.027; serum equol: r = 0.380, P = 0.004) among men with the TT genotype but not the CC or CT genotypes (r = -0.029 to -0.134, P = 0.091-0.717) for the CYP19 3'untranslated region (UTR) T-C polymorphism. Urinary and serum enterolactone showed similar genotype-dependent associations with testosterone but not with FAI. In this first study on phytoestrogen-gene associations in men, we conclude that enterolactone and equol are positively associated with plasma androgen concentrations, and interactions with CYP19 gene may be involved.

The biology of steroid hormones and endocrine treatment of breast cancer.

Recognition of the role of oestrogens in the stimulation of breast tumour growth has led to the development of several therapies based on endocrine intervention. Endocrine agents are currently used as a treatment for steroid receptor-positive breast cancer and more recently as a preventative measure in high-risk populations. Accurate quantification of resulting steroid hormonal profiles is essential to the understanding of the biological action and efficacy of these agents. In premenopausal women GnRH agonists suppress ovarian oestrogen synthesis and reduce oestradiol to close to postmenopausal levels. GnRH agonists used in combination with an aromatase inhibitor suppress levels even further. In contrast, tamoxifen can lead to markedly enhanced levels. In postmenopausal women aromatase inhibitors can achieve an almost complete inhibition of the aromatase enzyme.