Polymorphisms in hormone metabolism and growth factor genes and mammographic density in Norwegian postmenopausal hormone therapy users and non-users

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.

Interaction between Single Nucleotide Polymorphisms (SNP) of Tumor Necrosis Factor-Alpha (TNF-α) Gene and Plasma Arsenic and the Effect on Estimated Glomerular Filtration Rate (eGFR)

When poisons enter the human body, tumor necrosis factor (TNF-α) will increase and cause damage to tissues through oxidative stress or inflammatory reaction. In previous studies, arsenic (As) has known to cause many health problems. Some studies have shown that As exposure is negatively correlated with estimated glomerular filtration rate (eGFR), or with the prevalence of proteinuria. At present, there are few studies focusing on the effects of As exposure and TNF-α single nucleotide polymorphism (SNP) to eGFR; thus, this study was intended to explore the interactions between TNF-α SNPs and plasma As and their effects on eGFR. A cohort of 500 adults, aged 30 to 70 years, was randomly selected from Taiwan Biobank (TWB). We used the gene chip to screen out seven SNPs of the TNF-α gene and used the results, combined with questionnaires, biochemical tests, and stored plasma samples from the TWB, for the analysis of As by inductively coupled plasma mass spectrometry (ICP-MS). After adjustments for BMI, hypertension, hyperlipidemia, kidney stones, and smoking habits, multiple regression statistics were performed to explore the interaction between SNPs and plasma As with eGFR. In this sample of the general population, plasma As had a significant association with the decline of eGFR (β (SE) = −7.92 (1.70), p < 0.0001). TNF-α gene SNP rs1800629 had the property of regulating TNF-α, which interacts with plasma As; individuals with the AG type had a significantly lower eGFR than those with the GG type, by 9.59 mL/min/1.73 m2 (p < 0.05), which, regarding the dominant model, could infer that the A allele is a risk allele. SNP rs769177 had no interaction with plasma As; however, participants with the TT or TC type had significantly higher eGFR levels than the CC carriers, by 4.02 mL/min/1.73 m2 (p < 0.05). While rs769176 interacted with plasma As, if a person with the TC type had a higher plasma As concentration, that would sustain higher eGFR. This study found that certain SNPs of the TNF-α gene would be robust to the decline of eGFR caused by As exposure. Still, we need further research to confirm the protective regulation mechanism of these SNPs.

Survival-Associated Metabolic Genes and Risk Scoring System in HER2-Positive Breast Cancer

Human epidermal growth factor receptor 2 (HER2)-positive breast cancer and triple-negative breast cancer have their own genetic, epigenetic, and protein expression profiles. In the present study, based on bioinformatics techniques, we explored the prognostic targets of HER2-positive breast cancer from metabonomics perspective and developed a new risk score system to evaluate the prognosis of patients. By identifying the differences between HER2 positive and normal control tissues, and between triple negative breast cancer and normal control tissues, we found a large number of differentially expressed metabolic genes in patients with HER2-positive breast cancer and triple-negative breast cancer. Importantly, in HER2-positive breast cancer, decreased expression of metabolism-related genes ATIC, HPRT1, ASNS, SULT1A2, and HAL was associated with increased survival. Interestingly, these five metabolism-related genes can be used to construct a risk score system to predict overall survival (OS) in HER2-positive patients. The time-dependent receiver operating characteristic (ROC) curve analysis showed that the predictive sensitivity of the risk scoring system was higher than that of other clinical factors, including age, stage, and tumor node metastasis (TNM) stage. This work shows that specific transcriptional changes in metabolic genes can be used as biomarkers to predict the prognosis of patients, which is helpful in implementing personalized treatment and evaluating patient prognosis.

Single Nucleotide Polymorphism in Prolactin Gene Is Associated With Clinical Aggressiveness and Outcome of Canine Mammary Malignant Tumors

Prolactin (PRL) is a key hormone involved in canine mammary development and tumorigenesis. In this study, the influence of a single nucleotide polymorphism (SNP) in the PRL gene (rs23932236) on the clinicopathological parameters and survival of dogs with canine mammary tumors (CMTs) was investigated. A total of 206 female dogs with spontaneous mammary tumors were enrolled in this study and circulating blood cells were genotyped. This specific SNP was associated with larger size (>3 cm diameter) for malignant tumors (P = .036), tumors with infiltrative/invasive growth pattern (P = .010), vascular invasion (P = .006), and lymph node metastasis (P = .004). Carriers of the variant allele had a shorter overall survival compared to the wild-type population with an overall survival of 18.7 months and 22.7 months, respectively (P = .004). These findings suggest that SNP rs23932236 of canine PRL gene may be used as an indicator for the development of clinically aggressive forms of CMTs.

Exploring the Role of Breast Density on Cancer Prognosis among Women Attending Population-Based Screening Programmes

Background

Our aim was to assess the role of breast density on breast cancer mortality and recurrences, considering patient and tumour characteristics and the treatments received among women attending population-based screening programmes.

Methods

We conducted a retrospective cohort study among women aged 50-69 years attending population-based screening programmes, diagnosed with invasive breast cancer between 2000 and 2009, and followed up to 2014. Breast density was categorised as low density (≤25% dense tissue), intermediate density (25-50%), and high density (≥50%). Cox proportional hazards regression models were fitted to estimate the adjusted hazard ratios (aHR) and 95% confidence intervals (95% CI) for death and recurrences, adjusting by patient characteristics, mode of detection (screen-detected vs. interval cancer), and tumour features.

Results

The percentage of deaths and recurrences was higher among women with intermediate- and high-density breasts than among women with low-density breasts (p=0.011 for death; p=0.037 for recurrences). Adjusted Cox proportional hazards regression models revealed that women with intermediate- and high-density breasts had a higher risk of death than women with low-density breasts, being statistically significant for intermediate densities (aHR = 2.19 [95% CI: 1.16-4.13], aHR = 1.44 [95% CI: 0.67-3.1], respectively). No association was found between breast density and recurrences.

Conclusions

Breast density was associated with a higher risk of death, but not of recurrences, among women participating in breast cancer screening. These findings reinforce the need to improve screening sensitivity among women with dense breasts and to routinely assess breast density, not only for its role as a risk factor for breast cancer but also for its potential influence on cancer prognosis.

Mammographic density and breast tissue expression of inflammatory markers, growth factors, and vimentin

Background

Mammographic density is a known risk factor for breast cancer, but the underlying pathologic characteristics are not well understood. The current analysis investigated the expression of several markers of interest, e.g., inflammation and growth, with mammographic density (MD) in normal and malignant breast tissue specimens from 279 women of the Multiethnic Cohort (MEC).

Methods

Breast cancer cases, recruited from a nested case-control study within the MEC, provided mammograms for density evaluation. Protein expression (COX-2, TNF-α, TGF-β, IGF-1R, IGFBP-2, and vimentin) was assessed by immunohistochemical detection. Linear regression was applied to evaluate the relation between marker expression and percent density and to compute adjusted means with 95% confidence intervals (CI) by marker status while adjusting for confounders.

Results

Due to missing cores and tissue, normal tissue could only be evaluated for COX-2 and vimentin. No significant associations with mammographic density were detected for all markers analyzed. For inflammatory markers (TNF-α, COX-2, and TGF-β) in tumor tissue, MD were non-significantly higher with stronger expression but the differences were very small. For example, the mean MD values for no, weak, and strong TNF-α expression were 35% (95% CI 24–47%), 39% (95% CI 29–48%), and 38% (95% CI 27–50%). In a posthoc analysis among postmenopausal women only, the difference across categories of TNF-α expression increased to 25% (95% CI 12–39%), 35% (95% CI 23–48%), and 35% (95% CI 20–49%).

Conclusions

The current analysis offers little support for an involvement of immunohistochemical markers representing inflammatory and growth factor pathways as predictors of breast density.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5088-9) contains supplementary material, which is available to authorized users.

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.

Survival and Disease-Free Survival by Breast Density and Phenotype in Interval Breast Cancers

Background: We aimed to evaluate survival and disease-free survival in different subtypes of interval cancers by breast density, taking into account clinical and biological characteristics.Methods: We included 374 invasive breast tumors (195 screen-detected cancers; 179 interval cancers, classified into true interval, false-negatives, occult tumors and minimal-sign cancers) diagnosed in women ages 50-69 years undergoing biennial screening from 2000-2009, followed up to 2014. Breast density was categorized into non-dense (<25% dense tissue) and mixed dense breasts (≥25%). Survival curves were generated by the Kaplan-Meier method and compared by the log-rank test. Cox proportional hazard regression models were computed to estimate the adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs) for death and recurrences by comparing women with interval and true interval cancers versus women with screen-detected cancers, controlling for tumor and patient characteristics. All analyses were stratified by breast density.Results: Interval cancers were detected in younger women, at more advanced stages, in denser breasts and showed a higher proportion of triple-negative cancers, especially among true interval cancers. Women with interval cancer and non-dense breasts had an aHR for death of 3.40 (95% CI, 0.92-12.62). Women with true interval cancers detected in non-dense breasts had the highest adjusted risk of death (aHR, 6.55; 95% CI, 1.37-31.39).Conclusions: Women with true interval cancer in non-dense breasts had a higher risk of death than women with screen-detected cancers.Impact: These results support the advisability of routinely collecting information on breast density, both for further tailoring of screening strategies and as a prognostic factor for diagnosed breast cancers. Cancer Epidemiol Biomarkers Prev; 27(8); 908-16. ©2018 AACR.

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.

Vitamin D intake, month the mammogram was taken and mammographic density in Norwegian women aged 50-69

BACKGROUND

The role of vitamin D in breast cancer etiology is unclear. There is some, but inconsistent, evidence that vitamin D is associated with both breast cancer risk and mammographic density (MD). We evaluated the associations of MD with month the mammogram was taken, and with vitamin D intake, in a population of women from Norway--a country with limited sunlight exposure for a large part of the year.

METHODS

3114 women aged 50-69, who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004 or 2006/07, completed risk factor and food frequency (FFQ) questionnaires. Dietary and total (dietary plus supplements) vitamin D, calcium and energy intakes were estimated by the FFQ. Month when the mammogram was taken was recorded on the mammogram. Percent MD was assessed using a computer assisted method (Madena, University of Southern California) after digitization of the films. Linear regression models were used to investigate percent MD associations with month the mammogram was taken, and vitamin D and calcium intakes, adjusting for age, body mass index (BMI), study year, estrogen and progestin therapy (EPT), education, parity, calcium intakes and energy intakes.

RESULTS

There was no statistical significant association between the month the mammogram was taken and percent MD. Overall, there was no association between percent MD and quartiles of total or dietary vitamin D intakes, or of calcium intake. However, analysis restricted to women aged <55 years revealed a suggestive inverse association between total vitamin D intake and percent MD (p for trend = 0.03).

CONCLUSION

Overall, we found no strong evidence that month the mammogram was taken was associated with percent MD. We found no inverse association between vitamin D intake and percent MD overall, but observed a suggestive inverse association between dietary vitamin D and MD for women less than 55 years old.

Genome wide association study identifies a novel putative mammographic density locus at 1q12-q21

Mammographic density (MD) is an intermediate phenotype for breast cancer. Previous studies have identified genetic variants associated with MD; however, much of the genetic contribution to MD is unexplained. We conducted a two-stage genome-wide association analysis among the participants in the "Determinants of Density in Mammographies in Spain" study, together with a replication analysis in women from the Australian MD Twins and Sisters Study. Our discovery set covered a total of 3,351 Caucasian women aged 45 to 68 years, recruited from Spanish breast cancer screening centres. MD was blindly assessed by a single reader using Boyd's scale. A two-stage approach was employed, including a feature selection phase exploring 575,374 SNPs in 239 pairs of women with extreme phenotypes and a verification stage for the 183 selected SNPs in the remaining sample (2,873 women). Replication was conducted in 1,786 women aged 40 to 70 years old recruited via the Australian Twin Registry, where MD were measured using Cumulus-3.0, assessing 14 SNPs with a p value <0.10 in stage 2. Finally, two genetic variants in high linkage disequilibrium with our best hit were studied using the whole Spanish sample. Evidence of association with MD was found for variant rs11205277 (OR = 0.74; 95% CI = 0.67-0.81; p = 1.33 × 10(-10) ). In replication analysis, only a marginal association between this SNP and absolute dense area was found. There were also evidence of association between MD and SNPs in high linkage disequilibrium with rs11205277, rs11205303 in gene MTMR11 (OR = 0.73; 95% CI = 0.66-0.80; p = 2.64 × 10(-11) ) and rs67807996 in gene OTUD7B (OR = 0.72; 95% CI = 0.66-0.80; p = 2.03 × 10(-11)). Our findings provide additional evidence on common genetic variations that may contribute to MD.

Breast cancer susceptibility variants and mammographic density phenotypes in norwegian postmenopausal women

BACKGROUND

Mammographic density (MD) is one of the strongest known breast cancer risk factors. Twin studies have suggested that a large part of the variation in MD is genetically determined. We hypothesized that breast cancer susceptibility variants may affect MD, and that their effects may be modified by nongenetic factors.

METHODS

We assessed MD, using a computer-assisted method, on 2,348 postmenopausal Caucasian women (50-69 years) who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004 or 2006-07. We used linear regression (additive models) to determine the association between each SNP and MD, adjusting for age, body mass index (BMI), and study. We evaluated MD associations with 17 established breast cancer SNPs, overall, and by strata defined by non-genetic factors.

RESULTS

Two variants, 6q25.1-rs9383938 and TXNRD2-rs8141691, were statistically significantly associated with percent MD (P = 0.019 and 0.03, respectively), with the 6q25.1-rs9383938 association being consistent with the SNP effect on breast cancer risk. The effect of 6q25.1-rs3734805 on percent MD varied between parous and nulliparous women (Pinteraction = 0.02), whereas the effects of 9q31.2-rs865686 and MRPS30:FGF10-rs4415084 differed across strata of BMI (Pinteraction = 0.01 and 0.005, respectively). There was no evidence of effect modification by estrogen and progestin therapy use or alcohol consumption.

CONCLUSION

This study provides novel evidence of shared genetic risk factors between MD and breast cancer and of possible MD genetic-environmental interactions.

IMPACT

Although the results may be chance findings, they nevertheless highlight the need to investigate interactions with nongenetic factors in studies on the genetics of MD.

Aromatase inhibitor-induced modulation of breast density: clinical and genetic effects

Background:

Change in breast density may predict outcome of women receiving adjuvant hormone therapy for breast cancer. We performed a prospective clinical trial to evaluate the impact of inherited variants in genes involved in oestrogen metabolism and signalling on change in mammographic percent density (MPD) with aromatase inhibitor (AI) therapy.

Methods:

Postmenopausal women with breast cancer who were initiating adjuvant AI therapy were enrolled onto a multicentre, randomised clinical trial of exemestane vs letrozole, designed to identify associations between AI-induced change in MPD and single-nucleotide polymorphisms in candidate genes. Subjects underwent unilateral craniocaudal mammography before and following 24 months of treatment.

Results:

Of the 503 enrolled subjects, 259 had both paired mammograms at baseline and following 24 months of treatment and evaluable DNA. We observed a statistically significant decrease in mean MPD from 17.1 to 15.1% (P<0.001), more pronounced in women with baseline MPD ⩾20%. No AI-specific difference in change in MPD was identified. No significant associations between change in MPD and inherited genetic variants were observed.

Conclusion:

Subjects with higher baseline MPD had a greater average decrease in MPD with AI therapy. There does not appear to be a substantial effect of inherited variants in biologically selected candidate genes.

Variation in inflammatory cytokine/growth-factor genes and mammographic density in premenopausal women aged 50-55

Background

Mammographic density (MD) has been found to be an independent risk factor for breast cancer. Although data from twin studies suggest that MD has a strong genetic component, the exact genes involved remain to be identified. Alterations in stromal composition and the number of epithelial cells are the most predominant histopathological determinants of mammographic density. Interactions between the breast stroma and epithelium are critically important in the maturation and development of the mammary gland and the cross-talk between these cells are mediated by paracrine growth factors and cytokines. The potential impact of genetic variation in growth factors and cytokines on MD is largely unknown.

Methods

We investigated the association between 89 single nucleotide polymorphisms (SNPs) in 7 cytokine/growth-factor genes (FGFR2, IGFBP1, IGFBP3, TGFB1, TNF, VEGF, IL6) and percent MD in 301 premenopausal women (aged 50 to 55 years) participating in the Norwegian Breast Cancer Screening Program. We evaluated the suggestive associations in 216 premenopausal Singapore Chinese Women of the same age.

Results

We found statistically significant associations between 9 tagging SNPs in the IL6 gene and MD in Norwegian women; the effect ranged from 3–5% in MD per variant allele (p-values = 0.02 to 0.0002). One SNP in the IL6 (rs10242595) significantly influenced MD in Singapore Chinese women.

Conclusion

Genetic variations in IL6 may be associated with MD and therefore may be an indicator of breast cancer risk in premenopausal women.

Hormone metabolism genes and mammographic density in Singapore Chinese women

BACKGROUND

Female steroid hormone levels and exogenous hormone use influence breast cancer risk. We investigated the association between genetic variation in the hormone metabolism and signaling pathway and mammographic density, a strong predictor of breast cancer risk.

METHODS

We genotyped 161 SNPs in 15 hormone metabolism pathway gene regions and evaluated mammographic density in 2,038 Singapore Chinese women. Linear regression analysis was used to investigate single-nucleotide polymorphism (SNP) and mammographic density association. An overall pathway summary was obtained using the adaptive ranked truncated product test.

RESULTS

We did not find any of the individually tested SNPs to be associated with mammographic density after a multiple testing correction. There was no evidence of an overall effect on mammographic density of genetic variation in the hormone metabolism pathway.

CONCLUSIONS

In this cross-sectional study, genetic variation in hormone metabolism pathway was not associated with mammographic density in Singapore Chinese women.

IMPACT

Consistent with existing data from Caucasian populations, polymorphisms in hormone pathway genes are not likely to be strong predictors of mammographic density in Asian women.

Genetic variation in transforming growth factor beta 1 and mammographic density in Singapore Chinese women

TGF-β plays a critical role in normal mammary development and morphogenesis. Decreased TGF-β signaling has been associated with increased mammographic density. Percent mammographic density (PMD) adjusted for age and body mass index (BMI) is a strong risk factor and predictor of breast cancer risk. PMD is highly heritable, but few genetic determinants have been identified. We investigated the association between genetic variation in TGFB1 and PMD using a cross-sectional study of 2,038 women who were members of the population-based Singapore Chinese Health Study cohort. We assessed PMD using a computer-assisted method. We used linear regression to examine the association between nine tagging single-nucleotide polymorphisms (SNP) of TGFB1 and PMD and their interaction with parity, adjusting for age, BMI, and dialect group. We calculated P values adjusted for correlated tests (P(ACT)) to account for multiple testing. The strongest association was observed for rs2241716. Adjusted PMD was higher by 1.5% per minor allele (P(ACT) = 0.04). When stratifying by parity, this association was limited to nulliparous women. For nulliparous women, adjusted PMD was higher by 8.6% per minor allele (P(ACT) = 0.003; P for interaction with parity = 0.002). Three additional TGFB1 tagging SNPs, which were in linkage disequilibrium with rs2241716, were statistically significantly associated with adjusted PMD (P(ACT) < 0.05) for nulliparous women. However, none of these three SNPs showed statistically significant association after adjusting for rs2241716. Our data support that TGFB1 genetic variation may be an important genetic determinant of mammographic density measure that predicts breast cancer risk, particularly in nulliparous women.