Influence of estrogen receptor alpha and progesterone receptor polymorphisms on the effects of hormone therapy on mammographic density

Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review

BACKGROUND

Mammography Density (MD) is a potential risk marker that is influenced by genetic polymorphisms and can subsequently modulate the risk of breast cancer. This qualitative systematic review summarizes the genes and biological pathways involved in breast density and discusses the potential clinical implications in view of the genetic risk profile for breast density.

METHODS

The terms related to "Common genetic variations" and "Breast density" were searched in Scopus, PubMed, and Web of Science databases. Gene pathways analysis and assessment of protein interactions were also performed.

RESULTS

Eighty-six studies including 111 genes, reported a significant association between mammographic density in different populations. ESR1, IGF1, IGFBP3, and ZNF365 were the most prevalent genes. Moreover, estrogen metabolism, signal transduction, and prolactin signaling pathways were significantly related to the associated genes. Mammography density was an associated phenotype, and eight out of 111 genes, including COMT, CYP19A1, CYP1B1, ESR1, IGF1, IGFBP1, IGFBP3, and LSP1, were modifiers of this trait.

CONCLUSION

Genes involved in developmental processes and the evolution of secondary sexual traits play an important role in determining mammographic density. Due to the effect of breast tissue density on the risk of breast cancer, these genes may also be associated with breast cancer risk.

Type 2 Diabetes in Women: Differences and Difficulties

BACKGROUND

Lifestyle modification, along with medication, has improved the quality of life of patients with type 2 diabetes (T2D), but the treatment of diabetes in women still lacks a gender-centric approach.

METHODS

Expert opinions to improve diabetes management in women were collated from the open discussion forum organized by the sixth Jothydev's Professional Education Forum Diabetes Convention, which included global diabetes care experts and the general public. The review is also based on the studies published in electronic databases such as PubMed and Google Scholar that discussed the problems and challenges faced by the Indian diabetes care sector in treating women with diabetes.

RESULTS

The complex interplay of biological, socioeconomic, psychosocial, and physiological factors in women with type 2 diabetes has not been well addressed to date. Biological factors such as neurohumoral pathways, sex hormones, genetic predisposition as well as gender-based environmental and behavioural differences must be considered for modern personalized diabetes treatment. Most importantly, pregnant women with diabetes deserve special attention. This vulnerable phase has a marked impact on the future health of both the mother and the offspring.

CONCLUSION

The review provides an overview of the challenges and issues that exist in the clinical management of diabetes and its complications among women in India. Women-centric clinical approaches should be encouraged for the effective management of diabetes in Indian women.

Does circulating progesterone mediate the associations of single nucleotide polymorphisms in progesterone receptor (PGR)-related genes with mammographic breast density in premenopausal women?

Progesterone is a proliferative hormone in the breast but the associations of genetic variations in progesterone-regulated pathways with mammographic breast density (MD) in premenopausal women and whether these associations are mediated through circulating progesterone are not clearly defined. We, therefore, investigated these associations in 364 premenopausal women with a median age of 44 years. We sequenced 179 progesterone receptor (PGR)-related single nucleotide polymorphisms (SNPs). We measured volumetric percent density (VPD) and non-dense volume (NDV) using Volpara. Linear regression models were fit on circulating progesterone or VPD/NDV separately. We performed mediation analysis to evaluate whether the effect of a SNP on VPD/NDV is mediated through circulating progesterone. All analyses were adjusted for confounders, phase of menstrual cycle and the Benjamini-Hochberg false discovery (FDR) adjusted p-value was applied to correct for multiple testing. In multivariable analyses, only PGR rs657516 had a direct effect on VPD (averaged direct effect estimate = - 0.20, 95%CI = - 0.38 ~ - 0.04, p-value = 0.02) but this was not statistically significant after FDR correction and the effect was not mediated by circulating progesterone (mediation effect averaged across the two genotypes = 0.01, 95%CI = - 0.02 ~ 0.03, p-value = 0.70). Five SNPs (PGR rs11571241, rs11571239, rs1824128, rs11571150, PGRMC1 rs41294894) were associated with circulating progesterone but these were not statistically significant after FDR correction. SNPs in PGR-related genes were not associated with VPD, NDV and circulating progesterone did not mediate the associations, suggesting that the effects, if any, of these SNPs on MD are independent of circulating progesterone.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12672-021-00438-1.

Growth factor genes and change in mammographic density after stopping combined hormone therapy in the California Teachers Study

Background

The contribution of genetic polymorphisms to the large inter-individual variation in mammographic density (MD) changes following starting and stopping use of estrogen and progestin combined therapy (EPT) has not been well-studied. Previous studies have shown that circulating levels of insulin-like growth factors are associated with MD and cross-talk between estrogen signaling and growth factors is necessary for cell proliferation in the breast. We evaluated single nucleotide polymorphisms (SNPs) in growth factor genes in association with MD changes after women stop EPT use.

Methods

We genotyped 191 SNPs in 13 growth factor pathway genes in 284 non-Hispanic white California Teachers Study participants who previously used EPT and collected their mammograms before and after quitting EPT. Percent MD was assessed using a computer-assisted method. Change in percent MD was calculated by subtracting percent MD of an ‘off-EPT’ mammogram from percent MD of an ‘on-EPT’ (i.e. baseline) mammogram. We used multivariable linear regression analysis to investigate the association between SNPs and change in percent MD. We calculated P-values corrected for multiple testing within a gene (P_adj).

Results

Rs1983210 in INHA and rs35539615 in IGFBP1/3 showed the strongest associations. Per minor allele of rs1983210, the absolute change in percent MD after stopping EPT use decreased by 1.80% (a difference in absolute change in percent MD) (P_adj= 0.021). For rs35539615, change in percent MD increased by 1.79% per minor allele (P_adj= 0.042). However, after applying a Bonferroni correction for the number of genes tested, these associations were no longer statistically significant.

Conclusions

Genetic variation in growth factor pathway genes INHA and IGFBP1/3 may predict longitudinal MD change after women quit EPT. The observed differences in EPT-associated changes in percent MD in association with these genetic polymorphisms are modest but may be clinically significant considering that the magnitude of absolute increase in percent MD reported from large clinical trials of EPT ranged from 3% to 7%.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4981-6) contains supplementary material, which is available to authorized users.

Impact of CYP19A1 and ESR1 variants on early-onset side effects during combined endocrine therapy in the TEXT trial

Background

Single nucleotide polymorphisms (SNPs) in the estrogen receptor 1 (ESR1) and cytochrome P450 19A1 (CYP19A1) genes have been associated with breast cancer risk, endocrine therapy response and side effects, mainly in postmenopausal women with early breast cancer. This analysis aimed to assess the association of selected germline CYP19A1 and ESR1 SNPs with early-onset hot flashes, sweating and musculoskeletal symptoms in premenopausal patients enrolled in the Tamoxifen and Exemestane Trial (TEXT).

Methods

Blood was collected from consenting premenopausal women with hormone-responsive early breast cancer, randomly assigned to 5-years of tamoxifen plus ovarian suppression (OFS) or exemestane plus OFS. DNA was extracted with QIAamp kits and genotyped for two CYP19A1 (rs4646 and rs10046) and three ESR1 (rs2077647, rs2234693 and rs9340799) SNPs by a real-time pyrosequencing technique. Adverse events (AEs) were recorded at baseline and 3-monthly during the first year. Associations of the genotype variants with grade ≥2 early-onset targeted AEs of hot flashes/sweating or musculoskeletal events were assessed using logistic regression models.

Results

There were 2660 premenopausal patients with breast cancer in the intention-to-treat population of TEXT, and 1967 (74 %) are included in this translational study. The CYP19A1 rs10046 variant T/T, represented in 23 % of women, was associated with a reduced incidence of grade ≥2 hot flashes/sweating (univariate odds ratio (OR) = 0.78; 95 % CI 0.63–0.97; P = 0.03), more strongly in patients assigned exemestane + OFS (TT vs CT/CC: OR = 0.65, 95 % CI = 0.48–0.89) than assigned tamoxifen + OFS (OR = 0.94, 95 % CI = 0.69–1.27, interaction P = 0.03). No association with any of the CYP19A1/ESR1 genotypes and musculoskeletal AEs was found.

Conclusion

The CYP19A1 rs10046 variant T/T favors lower incidence of hot flashes/sweating under exemestane + OFS treatment, suggesting endocrine-mediated effects. Based on findings from others, this SNP may potentially enhance treatment adherence and treatment efficacy. We plan to evaluate the clinical impact of this polymorphism during time, pending sufficient median follow up.

Trial registration

ClinicalTrials.gov NCT00066703, registered August 6, 2003.

Polymorphisms in the estrogen receptor alpha gene (ESR1), daily cycling estrogen and mammographic density phenotypes

Background

Single nucleotide polymorphisms (SNPs) involved in the estrogen pathway and SNPs in the estrogen receptor alpha gene (ESR1 6q25) have been linked to breast cancer development, and mammographic density is an established breast cancer risk factor. Whether there is an association between daily estradiol levels, SNPs in ESR1 and premenopausal mammographic density phenotypes is unknown.

Methods

We assessed estradiol in daily saliva samples throughout an entire menstrual cycle in 202 healthy premenopausal women in the Norwegian Energy Balance and Breast Cancer Aspects I study. DNA was genotyped using the Illumina Golden Gate platform. Mammograms were taken between days 7 and 12 of the menstrual cycle, and digitized mammographic density was assessed using a computer-assisted method (Madena). Multivariable regression models were used to study the association between SNPs in ESR1, premenopausal mammographic density phenotypes and daily cycling estradiol.

Results

We observed inverse linear associations between the minor alleles of eight measured SNPs (rs3020364, rs2474148, rs12154178, rs2347867, rs6927072, rs2982712, rs3020407, rs9322335) and percent mammographic density (p-values: 0.002–0.026), these associations were strongest in lean women (BMI, ≤23.6 kg/m^2.). The odds of above-median percent mammographic density (>28.5 %) among women with major homozygous genotypes were 3–6 times higher than those of women with minor homozygous genotypes in seven SNPs. Women with rs3020364 major homozygous genotype had an OR of 6.46 for above-median percent mammographic density (OR: 6.46; 95 % Confidence Interval 1.61, 25.94) when compared to women with the minor homozygous genotype. These associations were not observed in relation to absolute mammographic density. No associations between SNPs and daily cycling estradiol were observed. However, we suggest, based on results of borderline significance (p values: 0.025–0.079) that the level of 17β-estradiol for women with the minor genotype for rs3020364, rs24744148 and rs2982712 were lower throughout the cycle in women with low (<28.5 %) percent mammographic density and higher in women with high (>28.5 %) percent mammographic density, when compared to women with the major genotype.

Conclusion

Our results support an association between eight selected SNPs in the ESR1 gene and percent mammographic density. The results need to be confirmed in larger studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-016-2804-1) contains supplementary material, which is available to authorized users.

A comprehensive evaluation of interaction between genetic variants and use of menopausal hormone therapy on mammographic density

INTRODUCTION

Mammographic density is an established breast cancer risk factor with a strong genetic component and can be increased in women using menopausal hormone therapy (MHT). Here, we aimed to identify genetic variants that may modify the association between MHT use and mammographic density.

METHODS

The study comprised 6,298 postmenopausal women from the Mayo Mammography Health Study and nine studies included in the Breast Cancer Association Consortium. We selected for evaluation 1327 single nucleotide polymorphisms (SNPs) showing the lowest P-values for interaction (P int) in a meta-analysis of genome-wide gene-environment interaction studies with MHT use on risk of breast cancer, 2541 SNPs in candidate genes (AKR1C4, CYP1A1-CYP1A2, CYP1B1, ESR2, PPARG, PRL, SULT1A1-SULT1A2 and TNF) and ten SNPs (AREG-rs10034692, PRDM6-rs186749, ESR1-rs12665607, ZNF365-rs10995190, 8p11.23-rs7816345, LSP1-rs3817198, IGF1-rs703556, 12q24-rs1265507, TMEM184B-rs7289126, and SGSM3-rs17001868) associated with mammographic density in genome-wide studies. We used multiple linear regression models adjusted for potential confounders to evaluate interactions between SNPs and current use of MHT on mammographic density.

RESULTS

No significant interactions were identified after adjustment for multiple testing. The strongest SNP-MHT interaction (unadjusted P int <0.0004) was observed with rs9358531 6.5kb 5' of PRL. Furthermore, three SNPs in PLCG2 that had previously been shown to modify the association of MHT use with breast cancer risk were found to modify also the association of MHT use with mammographic density (unadjusted P int <0.002), but solely among cases (unadjusted P int SNP×MHT×case-status <0.02).

CONCLUSIONS

The study identified potential interactions on mammographic density between current use of MHT and SNPs near PRL and in PLCG2, which require confirmation. Given the moderate size of the interactions observed, larger studies are needed to identify genetic modifiers of the association of MHT use with mammographic density.

Hormone metabolism pathway genes and mammographic density change after quitting estrogen and progestin combined hormone therapy in the California Teachers Study

INTRODUCTION

Mammographic density (MD) is a strong biomarker of breast cancer risk. MD increases after women start estrogen plus progestin therapy (EPT) and decreases after women quit EPT. A large interindividual variation in EPT-associated MD change has been observed, but few studies have investigated genetic predictors of the EPT-associated MD change. Here, we evaluate the association between polymorphisms in hormone metabolism pathway genes and MD changes when women quit EPT.

METHODS

We collected mammograms before and after women quit EPT and genotyped 405 tagging single nucleotide polymorphisms (SNPs) in 30 hormone metabolism pathway genes in 284 non-Hispanic white participants of the California Teachers Study (CTS). Participants were ages 49 to 71 years at time of mammography taken after quitting EPT. We assessed percent MD using a computer-assisted method. MD change was calculated by subtracting MD of an 'off-EPT' mammogram from MD of an 'on-EPT' (that is baseline) mammogram. Linear regression analysis was used to investigate the SNP-MD change association, adjusting for the baseline 'on-EPT' MD, age and BMI at time of baseline mammogram, and time interval and BMI change between the two mammograms. An overall pathway and gene-level summary was obtained using the adaptive rank truncated product (ARTP) test. We calculated 'P values adjusted for correlated tests (P(ACT))' to account for multiple testing within a gene.

RESULTS

The strongest associations were observed for rs7489119 in SLCO1B1, and rs5933863 in ARSC. SLCO1B1 and ARSC are involved in excretion and activation of estrogen metabolites of EPT, respectively. MD change after quitting was 4.2% smaller per minor allele of rs7489119 (P = 0.0008; P(ACT) = 0.018) and 1.9% larger per minor allele of rs5933863 (P = 0.013; P(ACT) = 0.025). These individual SNP associations did not reach statistical significance when we further used Bonferroni correction to consider the number of tested genes. The pathway level summary ARTP P value was not statistically significant.

CONCLUSIONS

Data from this longitudinal study of EPT quitters suggest that genetic variation in two hormone metabolism pathway genes, SLCO1B1 and ARSC, may be associated with change in MD after women stop using EPT. Larger longitudinal studies are needed to confirm our findings.

Measurement of breast density with digital breast tomosynthesis--a systematic review

Digital breast tomosynthesis (DBT) has gained acceptance as an adjunct to digital mammography in screening. Now that breast density reporting is mandated in several states in the USA, it is increasingly important that the methods of breast density measurement be robust, reliable and consistent. Breast density assessment with DBT needs some consideration since quantitative methods are modelled for two-dimensional (2D) mammography. A review of methods used for breast density assessment with DBT was performed. Existing evidence shows Cumulus has better reproducibility than that of the breast imaging reporting and data system (BI-RADS®) but still suffers from subjective variability; MedDensity is limited by image noise, whilst Volpara and Quantra are robust and consistent. The reported BI-RADs inter-reader breast density agreement (k) ranged from 0.65 to 0.91, with inter-reader correlation (r) ranging from 0.70 to 0.93. The correlation (r) between BI-RADS and Cumulus ranged from 0.54-0.94, whilst that of BI-RADs and MedDensity ranged from 0.48-0.78. The reported agreement (k) between BI-RADs and Volpara is 0.953. Breast density correlation between DBT and 2D mammography ranged from 0.73 to 0.97, with agreement (k) ranging from 0.56 to 0.96. To avoid variability and provide more reliable breast density information for clinicians, automated volumetric methods are preferred.

The expression of the estrogen receptor in obese patients with high breast density (HBD)

OBJECTIVE

Obesity has been associated with increased risk for breast cancer (BC) mortality. Verifying in women with high breast density (HBD) post-menopausal, the frequency of polymorphisms of estrogen receptor (ER)α-PvuII, ERα-XbaI and if they influence the body mass index (BMI).

METHODS

Study with 308 women with HBD post-menopause divided into two groups according to BMI: 1st group = BMI < 25 kg/m(2), 2nd group = BMI ≥ 25 kg/m(2). It was characterized in the clinical history: menarche, menopause, parity, family history of BC, smoking and alcohol intake.

RESULTS

Allele and genotype frequencies for the ERα-397-Pvull and ERα-351-XbaI: P = 43.99%, p = 56.01%, pp = 32.14%, Pp = 47.73%, PP = X = 20.13% and X = 41.56%, x = 58.44%; xx = 33.44%; Xx = 50.00%; XX = 16.56%, respectively. Both PvuII and XbaI influenced BMI. When XbaI is mutated the tendency is toward higher BMI (0.039), and women with lower BMI were more frequent in PvuII genotype (p = 0.002). More frequent risk factors for BC: menarche before the age of 12 years (35.38%), nulliparity or 1st child after 28 years old (41.66%), family history of BC (19.16%) and overweight/obesity (62.01%).

CONCLUSION

Variations in the ERα gene affected the BMI in women with HBD, who already are at increased risk for BC.

Polymorphisms of estrogen receptor-α gene in Brazilian women with high breast density after menopause

The association of genetic polymorphism in the estrogen receptor alpha (ERα) gene and risk for diseases including breast cancer (BC) has been the subject of great interest.

OBJECTIVE

Checking on women with high breast density after menopause, the frequency of the Pvull and Xbal polymorphisms of the ERα gene and the correlation between them and the known risk factors for breast cancer.

METHOD

Observational study with 308 women between 45 and 65 years old with high breast density, without hormonal therapy, menstruation for a year or more, breast and ovarian cancer history. It was characterized in clinical history and physical examination: menarche, menopause, parity, family history of BC, smoking, alcohol intake and body mass index.

RESULTS

The allelic and genotypic frequencies for ERα-Pvull and Xbal: p = 43.99%; p = 56.01%; pp = 32.14%; Pp = 47.73% and PP = 20.13%; X = 41.56%; x = 58.44%; xx = 33.44%; Xx = 50.00% and XX = 16.56%, respectively. The most frequent risk factors for BC: menarche before 12 years old (35.38%), nulliparity or first child after 28 years old (41.66%), family history of BC (19.16%) and overweight/obesity (62.01%).

CONCLUSION

Allelic and genotypic distribution similar to literature. The risk factors for BC were more prevalent in women with high breast density but without significant associations with these polymorphisms.

Oestrogen receptor alpha gene polymorphisms relationship with semen variables in infertile men

This study aimed to assess the association of oestrogen receptor alpha (ER-α) gene polymorphisms and semen variables in infertile oligoasthenoteratozoospermic (OAT) men. In all, 141 men were grouped into fertile men (n = 60) and infertile OAT men (n = 81). They were subjected to assessment of semen analysis, acrosin activity, serum reproductive hormones and genotyping of ER-α gene. Frequencies of p and x alleles in ER-α gene PvuII and XbaI polymorphisms were more prevalent among fertile men compared with infertile OAT men. Presence of P and X alleles was associated with increased incidence of male infertility for genotypes PP, XX compared with genotypes pp and xx (OR = 2.8; 95% CI: 2.36-6.97; P = 0.001 and OR = 4.1, 95% CI: 1.49-11.39; P = 0.001, respectively). The mean of semen variables and sperm acrosin activity were significantly higher in cases associated with pp than PP and in xx than XX genotypes of ER-α gene. Mean levels of all serum reproductive hormones demonstrated nonsignificant differences in different ER-α genotypes except oestrogen that was elevated in PP and XX ER-α gene genotypes. It is concluded that as oestrogen is concerned in male gamete maturation, ER-α gene polymorphisms might play a role in the pathophysiology of male infertility.

Progestogen levels, progesterone receptor gene polymorphisms, and mammographic density changes: results from the Postmenopausal Estrogen/Progestin Interventions Mammographic Density Study

OBJECTIVE

Estrogen plus progestin therapy (EPT) in postmenopausal women increases breast cancer risk and mammographic density to a higher extent than does estrogen therapy alone. Data from the randomized placebo-controlled Postmenopausal Estrogen/Progestinv Interventions trial showed that EPT-induced increases in serum estrone and estrone sulfate levels were positively correlated with increases in mammographic density. Here, after adjusting for serum estrone and estrone sulfate levels, we investigated the roles of posttreatment serum progestogen increase and of progesterone receptor gene (PGR) genetic variations on changes in mammographic density.

METHODS

We measured the percent mammographic density and serum progestogen levels in 280 Postmenopausal Estrogen/Progestin Interventions trial participants randomized to EPT treatment. Analyses of genetic variations in PGR were limited to 260 white women for whom we successfully obtained PGR genotypes. We used linear regression analyses to determine how an increase in progestogen levels and PGR genetic variation influenced mammographic density change after EPT.

RESULTS

The increase in posttreatment serum progestogen level was positively associated with greater increases in mammographic density after adjustment for covariates (P trend = 0.044). Compared with women in the lowest quartile of serum progestogen level, women in the highest quartile experienced a 3.5% greater increase in mammographic density (P = 0.046). We did not find a strong indication that genetic variation in PGR was associated with mammographic density increase or modified the association with serum progestogen; however, confidence in these null findings is constrained by our small sample size.

CONCLUSIONS

Our results suggest that higher serum progestogen levels resulting from EPT treatment lead to greater increases in mammographic density.

Prevalence of ERα-397 PvuII C/T, ERα-351 XbaI A/G and PGR PROGINS polymorphisms in Brazilian breast cancer-unaffected women

Polymorphisms of hormone receptor genes have been linked to modifications in reproductive factors and to an increased risk of breast cancer (BC). In the present study, we have determined the allelic and genotypic frequencies of the ERα-397 PvuII C/T, ERα-351 XbaI A/G and PGR PROGINS polymorphisms and investigated their relationship with mammographic density, body mass index (BMI) and other risk factors for BC. A consecutive and unselected sample of 750 Brazilian BC-unaffected women enrolled in a mammography screening program was recruited. The distribution of PGR PROGINS genotypic frequencies was 72.5, 25.5 and 2.0% for A1A1, A1A2 and A2A2, respectively, which was equivalent to that encountered in other studies with healthy women. The distribution of ERα genotypes was: ERα-397 PvuII C/T: 32.3% TT, 47.5% TC, and 20.2% CC; ERα-351 XbaI A/G: 46.3% AA, 41.7% AG and 12.0% GG. ERα haplotypes were 53.5% PX, 14.3% Px, 0.3% pX, and 32.0% px. These were significantly different from most previously published reports worldwide (P < 0.05). Overall, the PGR PROGINS genotypes A2A2 and A1A2 were associated with fatty and moderately fatty breast tissue. The same genotypes were also associated with a high BMI in postmenopausal women. In addition, the ERα-351 XbaI GG genotype was associated with menarche ≥12 years (P = 0.02). ERα and PGR polymorphisms have a phenotypic effect and may play an important role in BC risk determination. Finally, if confirmed in BC patients, these associations could have important implications for mammographic screening and strategies and may be helpful to identify women at higher risk for the disease.

Mammographic Density, Response to Hormones, and Breast Cancer Risk

Background

Percent mammographic density (PMD) is a strong risk factor for breast cancer that changes in response to changes in hormone exposure. We have examined the magnitude of the association of hormone exposure with PMD according to subsequent breast cancer risk.

Methods

In three case-control studies, with 1,164 patient cases and 1,155 controls nested in cohorts of women screened with mammography, we examined the association of PMD measured in the baseline mammogram with risk of breast cancer in the following 1 to 8 years (mean, 3 years), according to use of oral contraceptives (OCs) in premenopausal women, menopause, and hormone therapy (HT) in postmenopausal women. All statistical comparisons are adjusted for age and other risk factors.

Results

In premenopausal women who later developed breast cancer (patient cases), PMD was 5.3% greater in past users of OCs than in nonusers (P = .06). In controls, OC users had 2% less density than nonusers (P = .44; test for interaction P = .06). The difference in PMD between premenopausal and postmenopausal women for patient cases was 8.5% (P < .001) and for controls, 3.9% (P = .01; test for interaction P = .03). In postmenopausal women, PMD was 6% greater in patients who used HT than in never users (P < .001). Controls who used HT had 1.6% greater PMD (P = .26) than never users (test for interaction P = .001). Differences in PMD resulted mainly from differences in the dense area of the mammogram.

Conclusion

Differences in PMD associated with differences in hormone exposure were greater in women who later developed breast cancer than in controls in each of the hormone exposures examined.

Polymorphisms in genes involved in the estrogen pathway and mammographic density

Background

Single 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.

Methods

Polymorphisms 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 (P_trend) and interactions (P_i).

Results

None 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 (P_trend = 0.004), while no association was observed among parous women (P_trend = 0.62; P_i = 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 (P_trend = 0.06 and P_trend = 0.04, respectively), but with a decrease in AD among past hormonal derivatives users (P_trend = 0.04; P_i = 0.02 and P_trend = 0.08; P_i = 0.01, respectively). Moreover, a negative association of rs598126 HSD17B1 SNP with AD was observed among women with higher BMI (>median) (P_trend = 0.01; P_i = 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 (P_trend = 0.02; P_i = 0.03) or with late age at menarche (>median) (P_trend = 0.03; P_i = 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.

Conclusion

SNPs 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.

+331G/A variant in the progesterone receptor gene, postmenopausal hormone use and risk of breast cancer

A functional promoter polymorphism in the progesterone receptor (PR) gene previously has been associated with an increased risk of postmenopausal breast cancer. Whether the relationship between genetic variation in PR and risk of breast cancer is modified by postmenopausal hormone (PMH) use is unknown. Thus, we conducted a case-control study nested within the prospective Nurses' Health Study to evaluate if the risk of breast cancer associated with having the +331 A risk allele was modified by PMH use. Genotyping of this SNP was available for 1,664 postmenopausal breast cancer cases and 2,391 controls. Logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for breast cancer. Women who were carriers of 1 or both variant A alleles had a 31% increased risk of developing breast cancer (95% CI 1.04-1.65). PMH use significantly modified the association between the +331G/A polymorphism and risk (p-interaction <0.05). Among never users of PMH, women who were variant carriers had a significantly increased risk of breast cancer compared to those with the wild-type genotype (OR = 2.57; 95% CI 1.64-4.02). The +331G/A polymorphism was not associated with breast cancer risk among past (OR = 1.23; 95% CI 0.77-1.97) or current (OR = 1.14; 95% CI 0.84-1.56) PMH users. The data from this large prospective study provide evidence for a 2-fold increased risk of developing postmenopausal breast cancer among never users of PMH with the +331G/A SNP. This finding adds to the evidence that the PR has an important etiologic role in breast cancer and should be evaluated in future studies.

Sex steroid metabolism polymorphisms and mammographic density in pre- and early perimenopausal women

Introduction

We examined the association between mammographic density and single-nucleotide polymorphisms (SNPs) in genes encoding CYP1A1, CYP1B1, aromatase, 17β-HSD, ESR1, and ESR2 in pre- and early perimenopausal white, African-American, Chinese, and Japanese women.

Methods

The Study of Women's Health Across the Nation is a longitudinal community-based cohort study. We analyzed data from 451 pre- and early perimenopausal participants of the ancillary SWAN Mammographic Density study for whom we had complete information regarding mammographic density, genotypes, and covariates. With multivariate linear regression, we examined the relation between percentage mammographic breast density (outcome) and each SNP (primary predictor), adjusting for age, race/ethnicity, parity, cigarette smoking, and body mass index (BMI).

Results

After multivariate adjustment, the CYP1B1 rs162555 CC genotype was associated with a 9.4% higher mammographic density than the TC/TT genotype (P = 0.04). The CYP19A1 rs936306 TT genotype was associated with 6.2% lower mammographic density than the TC/CC genotype (P = 0.02). The positive association between CYP1A1 rs2606345 and mammographic density was significantly stronger among participants with BMI greater than 30 kg/m² than among those with BMI less than 25 kg/m² (P_interaction = 0.05). Among white participants, the ESR1 rs2234693 CC genotype was associated with a 7.0% higher mammographic density than the CT/TT genotype (P = 0.01).

Conclusions

SNPs in certain genes encoding sex steroid metabolism enzymes and ESRs were associated with mammographic density. Because the encoded enzymes and ESR1 are expressed in breast tissue, these SNPs may influence breast cancer risk by altering mammographic density.

Gene polymorphisms that may influence the biological effects of progestins

Many of the biological actions of progestins depend on binding to intracellular receptors and through a long chain of events to subsequent stimulation of transcriptional activity and protein synthesis. This process requires at least a few hours in time and many different proteins called coregulators do play a role after binding to the receptor. Evidence for polymorphisms in the gene coding for the PR has been obtained and many studies have already attempted to show associations between particular polymorphisms and human diseases. However, at present no consistent and conclusive picture has emerged on clinically important associations. Studies on links between polymorphisms in genes coding for coregulators are just beginning. The second pathway, the so-called non-genomic actions, is related to rapid effects of progestins that occur within minutes. At this moment a number of different membrane bound receptors have been identified. No data are available yet on polymorphisms in genes coding for these proteins or to link any of these membrane receptors to specific human pathology.

Can genes for mammographic density inform cancer aetiology?

Mammographic density (MD) reflects variations in fat, stromal and epithelial tissues that are thought to be regulated by several genes. High MD is an established risk factor for breast cancer; therefore, genes that regulate MD may indirectly influence breast cancer. These genes might also be fewer in number and easier to identify than those for breast cancer risk outside of inherited predisposition syndromes. In this Perspective, we review the limited genetic studies of MD and propose future directions.

Polymorphisms in genes involved in sex hormone metabolism, estrogen plus progestin hormone therapy use, and risk of postmenopausal breast cancer

Hormone therapy, estrogen plus progestin (E+P) particularly, is associated with increased risk of breast cancer. Functionally relevant polymorphisms in genes involved in sex hormone metabolism may alter exposure to exogenous sex hormones and affect risk of postmenopausal breast cancer. We evaluated associations of common polymorphisms in genes involved in estrogen and/or progesterone metabolism, E+P use, and their interactions with breast cancer risk in a case-control study of postmenopausal women (324 cases; 651 controls) nested within the VITAL cohort. None of the polymorphisms studied was, by itself, statistically significantly associated with breast cancer risk. E+P use was significantly associated with increased breast cancer risk (> or =10 years versus never; odds ratio, 1.9; 95% confidence interval, 1.3-2.8; P(trend) = 0.0002). Statistically significant interactions between CYP1A1 Ile(462)Val (P(interaction) = 0.04), CYP1A1 MspI (P(interaction) = 0.003), CYP1B1 Val(432)Leu (P(interaction) = 0.007), CYP1B1 Asn(453)Ser (P(interaction) = 0.04) and PGR Val(660)Leu (P(interaction) = 0.01), and E+P use were observed. The increased risk of breast cancer associated with E+P use was greater among women with at least one rare allele of the CYP1A1 Ile(462)Val, CYP1A1 MspI, CYP1B1 Asn(453)Ser, and PGR Val(660)Leu polymorphisms than among women homozygous for the common allele of these polymorphisms. Risk of breast cancer increased little with increasing years of E+P use among women with at least one CYP1B1 Val(432) allele; a large increase in risk was seen among women homozygous for CYP1B1 Leu(432). Our results support the hypothesis that specific polymorphisms in genes involved in sex hormone metabolism may modify the effect of E+P use on breast cancer risk.

Mammographic density. Potential mechanisms of breast cancer risk associated with mammographic density: hypotheses based on epidemiological evidence

There is now extensive evidence that mammographic density is an independent risk factor for breast cancer that is associated with large relative and attributable risks for the disease. The epidemiology of mammographic density, including the influences of age, parity and menopause, is consistent with it being a marker of susceptibility to breast cancer, in a manner similar to the concept of 'breast tissue age' described by the Pike model. Mammographic density reflects variations in the tissue composition of the breast. It is associated positively with collagen and epithelial and nonepithelial cells, and negatively with fat. Mammographic density is influenced by some hormones and growth factors as well as by several hormonal interventions. It is also associated with urinary levels of a mutagen. Twin studies have shown that most of the variation in mammographic density is accounted for by genetic factors. The hypothesis that we have developed from these observations postulates that the combined effects of cell proliferation (mitogenesis) and genetic damage to proliferating cells by mutagens (mutagenesis) may underlie the increased risk for breast cancer associated with extensive mammographic density. There is clearly a need for improved understanding of the specific factors that are involved in these processes and of the role played by the several breast tissue components that contribute to density. In particular, identification of the genes that are responsible for most of the variance in percentage density (and of their biological functions) is likely to provide insights into the biology of the breast, and may identify potential targets for preventative strategies in breast cancer.

Common genetic variation in the IGF-1 gene, serum IGF-I levels and breast density

INTRODUCTION

High breast density is one of the strongest known risk factors for developing breast cancer. Insulin-like growth factor I (IGF-I) is a strong mitogen and has been suggested to increase breast cancer risk by increasing the amount of dense tissue in the female breast.

OBJECTIVES

We wanted to investigate the effect of common variation in the IGF-1 gene on serum IGF-I levels and on breast density.

DESIGN AND METHODS

Mammograms and blood samples of 1,928 premenopausal participants of the Dutch Prospect-EPIC cohort were collected at baseline. Using a haplotype tagging approach, 16 single nucleotide polymorphisms (SNP) from three blocks covering the IGF-1 gene were genotyped in all study participants. Breast density was assessed using a quantitative computer-assisted method. For a subgroup of women, who went through menopause within 5 years after recruitment (n=656), premenopausal IGF-I levels and additionally postmenopausal breast density were determined. False positive report probabilities (FPRP) for statistically significant relations were calculated using the Wacholder method.

RESULTS

The minor alleles of five SNPs in block 3 were significantly associated with elevated levels of IGF-I (rs9989002, rs2033178, rs7136446, rs978458, rs6220; P-values: 0.01-0.04). The same SNPs were related with modestly higher percent breast density before menopause and-in the subgroup of women that became postmenopausal during follow-up-with a modestly higher percent breast density after menopause. The most significant result, i.e. the relation between rs6220 and IGF-I levels, had an FPRP<0.5 assuming prior probabilities of 0.01 and higher.

CONCLUSION

Common genetic variation in the IGF-1 gene is related to circulating levels of IGF-I, but the relationship with breast density is indecisive.

Strong Evidence of a Genetic Determinant for Mammographic Density, a Major Risk Factor for Breast Cancer

Increased mammographic density (MD), the proportion of dense tissue visible on a mammogram, is a strong risk factor for breast cancer, common in the population and clusters in families. We conducted the first genome-wide linkage scan to identify genes influencing MD. DNA was obtained from 889 relatives (756 women, 133 men) from 89 families. Percent MD was estimated on 618 (82%) female family members using a validated computer-assisted thresholding method. The genome-wide scan included 403 microsatellite DNA markers with an average spacing of 9 cM. Fine mapping of a region of chromosome 5p (5p13.1-5p15.1) was done using 21 additional closely spaced DNA markers. Linkage analyses were conducted to quantify the evidence for a gene responsible for MD across the genome. The maximum log odds for linkage (LOD) score from the genome-wide scan was on chromosome 5p (LOD = 2.9, supporting linkage by a factor of 10(2.9) or 794 to 1) with a 1-LOD interval spanning 28.6 cM. Two suggestive regions for linkage were also identified on chromosome 12 (LOD = 2.6, 1-LOD interval of 14.8 cM; and LOD = 2.5, 1-LOD interval of 17.2 cM). Finer mapping of the region surrounding the maximum LOD on chromosome 5p resulted in stronger and statistically significant evidence for linkage (LOD = 4.2) and a narrowed 1-LOD interval (13.4 cM). The putative locus on chromosome 5p is likely to account for up to 22% of variation in MD. Hence, 1 or more of the 45 candidate genes in this region could explain a large proportion of MD and, potentially, breast cancer.

A comparison of some anthropometric parameters between an Italian and a UK population: "proof of principle" of a European project using MammoGrid

AIM

To demonstrate the use of grid technology to produce a database of mammograms and supporting patient data, specifically using breast density as a biomarker of risk for breast cancer, for epidemiological purposes.

METHOD

The cohort comprised 1737 women from the UK and Italy, aged 28-87 years, mean 54.7 years, who underwent mammography after giving consent to the use of their data in the project. Information regarding height, weight, and exposure data (mAs and kV) was recorded. The computer program Generate-SMF was applied to all films in the database to measure breast volume, dense breast volume, and thereby percentage density. Visual readings of density using a six-category classification system were also available for 596 women.

RESULTS

The UK and Italian participants were similar in height, but the UK women were significantly heavier with a slightly higher body mass index (BMI), despite being younger. Both absolute and percentage breast density were significantly higher in the Udine cohort. Images from the medio-lateral projection (MLO) give a significantly lower percentage density than cranio-caudal (CC) images (p<0.0001). Total breast volume is negatively associated with percentage density, as are BMI and age (p<0.0001 for all), although 80% of the variability in percentage density remains unexplained.

CONCLUSION

The study offers proof of principle that confederated databases generated using Grid technology provide a useful and adaptable environment for large quantities of image, numerical, and qualitative data suitable for epidemiological research using the example of mammographic density as a biomarker of risk for breast cancer.

Steroid hormone receptor gene polymorphisms and osteoporosis: a pharmacogenomic review

Osteoporosis is a common skeletal disorder with a strong genetic component. In recent years, significant progress has been made in understanding the genetic basis of osteoporosis. Given the biological significance of signalling through steroid hormone receptors, bone biology and calcium homeostasis, alleles of steroid hormone receptor genes have been postulated to contribute to the well-documented genetic predisposition to osteoporosis; and in different studies, these alleles have been associated with variation in bone mass and fracture risk. Even though results are still conflicting and the molecular mechanisms by which these polymorphisms influence receptor activity remain, in part, to be investigated, an additional important issue is represented by potential pharmacogenomic (the investigation of variations of DNA or RNA characteristics as related to drug response) or pharmacogenetic (the influence of variations of DNA sequence on drug response) implications. In fact, steroid hormone receptors actually mediate the action of several compounds known to positively or negatively affect bone homeostasis, such as vitamin D, estrogen and glucocorticoids. This review analyses major pharmacogenetic studies of polymorphisms in steroid hormone receptor genes.