Association between estrogen receptor gene polymorphisms and breast density in postmenopausal women

Ramos, E. H. de Moura; Elias, Simone; Silva, I.; Nazário, Afonso Celso Pinto; Facina, Gil; Costa, Ana Maria; Carvalho, Cristina Valletta de; Nogueira-de-Souza, Naiara Correa

doi:10.3109/13697130902952585

Cited by 9 publications

(8 citation statements)

References 37 publications

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“…The distributions of selected demographic characteristics that are the main risk factors for breast cancer are presented in Table 3. It was observed elevated risk of HMD for the main risk factors that have been reported in other previous studies [20,16].…”

Section: Resultssupporting

confidence: 74%

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Polymorphisms in the Estrogen Receptor Alpha Gene and Mammographic Density Result Study in Brazilian Women

Souza¹,

Fonseca²,

Bagnoli³

et al. 2013

J Cancer Sci Ther

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This article presents the results of the case-control study in the city of São Paulo, that examined the association of the polymorphisms in the genes ERα-PvuII and ERα-XbaI with the risk of high mammographic density after menopause. The associations of these polymorphisms with other risk factors for breast cancer were also evaluated. MethodsCase-control study that included 308 women with HMD(for more than 50% density) and 155 controls(to 50% density or less) evaluated by computerized objective method [25], aged 45-65, without menstruation or hormone therapy for at least 1 year, without previous BC and ovarian cancer. Initially, the patients were selected in a subjective way by the standard ACR-BIRADS ® , by a unique reader (the head

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Section: Resultssupporting

confidence: 74%

“…The variables that entered in the model were those presented in the bivariate analyzes values p<0. 20. In all statistical tests were adopted a significance level of 5% (p<0.05).…”

Section: Introductionmentioning

confidence: 99%

Polymorphisms in the Estrogen Receptor Alpha Gene and Mammographic Density Result Study in Brazilian Women

Souza¹,

Fonseca²,

Bagnoli³

et al. 2013

J Cancer Sci Ther

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“…Up to now, the association between SNPs in ER genes and MD has been inconsistent [22,24,26,27,33]. Crandall et al found no association between SNP rs9340799 ( ERα ) or rs1256049 ( ERβ ) and MD among premenopausal women but the genotype homozygote for the rare allele of SNP rs2234693 ( ERα ) was related to a higher MD [33].…”

Section: Discussionmentioning

confidence: 99%

“…Among a population composed of premenopausal and postmenopausal women, MD was not related to ERα rs2234693 SNP but it had a negative association with the rare allele of rs9340799 SNP [26]. Among postmenopausal women, no association was found for ERα rs2234693 [22] or rs2077647 [24] SNP and MD, but the rare allele of rs9340799 SNP was related to a higher MD [24]. …”

Section: Discussionmentioning

confidence: 99%

Polymorphisms in genes involved in the estrogen pathway and mammographic density

Dumas

Diorio

2010

BMC Cancer

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BackgroundSingle nucleotide polymorphisms (SNPs) in genes involved in the estrogen pathway appear to be associated with breast cancer risk and possibly with mammographic density (MD), but little is known of these associations among premenopausal women. This study examines the association of 11 polymorphisms in five estrogen-related genes (estrogen receptors alpha and beta (ERα, ERβ), 17β-hydroxysteroid dehydrogenase 1 (HSD17B1), catechol-O-methyltransferase (COMT), cytochrome P450 1B1 (CYP1B1)) with premenopausal MD. Effect modification of four estrogen-related factors (parity, age at menarche, hormonal derivatives use and body mass index (BMI)) on this relation is also assessed.MethodsPolymorphisms were genotyped in 741 premenopausal Caucasian women whose MD was measured in absolute density (AD, cm2) and percent density using a computer-assisted method. Multivariate linear models were used to examine the associations (Ptrend) and interactions (Pi).ResultsNone of the SNPs showed a statistically significant association with AD. However, each additional rare allele of rs1056836 CYP1B1 was associated with a reduction in AD among nulliparous women (Ptrend = 0.004), while no association was observed among parous women (Ptrend = 0.62; Pi = 0.02). An increase in the number of rare alleles of the HSD17B1 SNP (rs598126 and rs2010750) was associated with an increase in AD among women who never used hormonal derivatives (Ptrend = 0.06 and Ptrend = 0.04, respectively), but with a decrease in AD among past hormonal derivatives users (Ptrend = 0.04; Pi = 0.02 and Ptrend = 0.08; Pi = 0.01, respectively). Moreover, a negative association of rs598126 HSD17B1 SNP with AD was observed among women with higher BMI (>median) (Ptrend = 0.01; Pi = 0.02). A negative association between an increased number of rare alleles of COMT rs4680 SNP and AD was limited to women who never used hormonal derivatives (Ptrend = 0.02; Pi = 0.03) or with late age at menarche (>median) (Ptrend = 0.03; Pi = 0.02). No significant association was observed between polymorphisms in the ERα or ERβ genes and AD. Similar results, although less significant, were observed when MD was assessed in percent density.ConclusionSNPs located in CYP1B1, COMT or HSD17B1 genes seem to be associated with MD in some strata of estrogen-related factors. Our findings suggest that modifying effects of estrogen-related factors should be considered when evaluating associations of polymorphisms in estrogen-related genes with premenopausal mammographic density.

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“…There are seven active members -UGT2B4, UGT2B7, UGT2B10, UGT2B11, UGT2B15, UGT2B17, UGT2B28 in the UGT2B gene clusters located on chromosome 4, which are mainly expressed in liver, breast, prostate, colon, and kidney. 22,23 Numerous studies [24][25][26][27] have shown that exposure to increased concentrations of estrogens, androgens, and progesterone may contribute to the development of breast cancer and other hormone-dependent cancers. Since UGT2B enzymes play an important role in the metabolism of steroid hormones, it has been proposed that variations in the UGT2B enzymes may contribute to the development of breast cancer.…”

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confidence: 99%

Pilot study demonstrating potential association between breast cancer image‐based risk phenotypes and genomic biomarkers

Giger

Sun

et al. 2014

Medical Physics

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Purpose: In this pilot study, the authors examined associations between image-based phenotypes and genomic biomarkers. The potential genetic contribution of UGT2B genes to interindividual variation in breast density and mammographic parenchymal patterns is demonstrated by performing an association study between image-based phenotypes and genomic biomarkers [single-nucleotide polymorphism (SNP) genotypes]. Methods: This candidate-gene approach study included 179 subjects for whom both mammograms and blood DNA samples had been obtained. The full-field digital mammograms were acquired using a GE Senographe 2000D FFDM system (12-bit; 0.1 mm-pixel size). Regions-of-interest, 256 × 256 pixels in size, selected from the central breast region behind the nipple underwent computerized image analysis to yield image-based phenotypes of mammographic density and parenchymal texture patterns. SNP genotyping was performed using a Sequenom MassArray System. One hundred twenty three SNPs with minor allele frequency above 5% were genotyped for the UGT2B gene clusters, and used in the study. The association between the image-based phenotypes and genomic biomarkers was assessed with the Pearson correlation coefficient via the PLINK software, and included permutation and correction for multiple SNP comparisons. Results: From the phenotype-genotype association analysis, a parenchyma texture coarseness feature was found to be correlated with SNP rs451632 after multiple test correction for the multiple SNPs (p = 0.022). The power law β, which is used to characterize the frequency component of texture patterns, was found to be correlated with SNP rs4148298 (p = 0.035). Conclusions:The authors' results indicate that UGT2B gene variation may contribute to interindividual variation in mammographic parenchymal patterns and breast density. Understanding the relationship between image-based phenotypes and genomic biomarkers may help understand the biologic mechanism for image-based biomarkers and yield a future role in personalized medicine.

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Association between estrogen receptor gene polymorphisms and breast density in postmenopausal women

Cited by 9 publications

References 37 publications

Polymorphisms in the Estrogen Receptor Alpha Gene and Mammographic Density Result Study in Brazilian Women

Polymorphisms in the Estrogen Receptor Alpha Gene and Mammographic Density Result Study in Brazilian Women

Polymorphisms in genes involved in the estrogen pathway and mammographic density

Pilot study demonstrating potential association between breast cancer image‐based risk phenotypes and genomic biomarkers

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