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

ABSTRACT: INTRODUCTION:Mammographic density (MD) is one of the strongest known breast cancer risk factors. Estrogen and progestin therapy (EPT) has been associated with increases in MD. Dense breast tissue is characterized by increased stromal tissue and (to a lesser degree) increased numbers of breast epithelial cells. It is possible that genetic factors modify the association between EPT and MD, and that certain genetic variants are particularly important in determining MD in hormone users. We evaluated the association between MD and 340 tagging single nucleotide polymorphisms (SNPs) from about 30 candidate genes in hormone metabolism/growth factor pathways among women who participated in the Norwegian Breast Cancer Screening Program (NBCSP) in 2004. METHODS:We assessed MD on 2,036 postmenopausal women aged 50 to 69 years using a computer-assisted method (Madena, University of Southern California) in a cross-sectional study. We used linear regression to determine the association between each SNP and MD, adjusting for potential confounders. The postmenopausal women were stratified into HT users (EPT and estrogen-only) and non-users (never HT). RESULTS:For current EPT users, there was an association between a variant in the prolactin gene (PRL; rs10946545) and MD (dominant model, Bonferroni-adjusted P (Pb) = 0.0144). This association remained statistically significant among current users of norethisterone acetate (NETA)-based EPT, a regimen common in Nordic countries. Among current estrogen-only users (ET), there was an association between rs4670813 in the cytochrome P450 gene (CYP1B1) and MD (dominant model, Pb = 0.0396). In never HT users, rs769177 in the tumor necrosis factor (TNF) gene and rs1968752 in the region of the sulfotransferase gene (SULT1A1/SULT1A2), were significantly associated with MD (Pb = 0.0202; Pb = 0.0349). CONCLUSIONS:We found some evidence that variants in the PRL gene were associated with MD in current EPT and NETA users. In never HT users, variants in the TNF and SULT1A1/SULT1A2 genes were significantly associated with MD. These findings may suggest that several genes in the hormone metabolism and growth factor pathways are implicated in determining MD.

SUBMITTER: Ellingjord-Dale M

PROVIDER: S-EPMC4053113 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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

Ellingjord-Dale Merete M Lee Eunjung E Couto Elisabeth E Ozhand Ali A Qureshi Samera S Hofvind Solveig S Van Den Berg David J DJ Akslen Lars A LA Grotmol Tom T Ursin Giske G

Breast cancer research : BCR 20121027 5

<h4>Introduction</h4>Mammographic density (MD) is one of the strongest known breast cancer risk factors. Estrogen and progestin therapy (EPT) has been associated with increases in MD. Dense breast tissue is characterized by increased stromal tissue and (to a lesser degree) increased numbers of breast epithelial cells. It is possible that genetic factors modify the association between EPT and MD, and that certain genetic variants are particularly important in determining MD in hormone users. We e ...[more]

PMID: 23095343

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Project description:Mammographic breast density (MBD) is a risk factor for breast cancer, but its molecular basis is poorly understood. Growth factors stimulate cellular and epithelial proliferation and could influence MBD via these mechanisms. Studies investigating the associations of circulating growth factors with MBD have, however, yielded conflicting results especially in postmenopausal women. We, therefore, investigated the associations of plasma growth factor gene expression [insulin-like growth factor (IGF)-1, IGF-binding protein 3, FGF-1, FGF-12, TGFβ1 and bone morphogenetic protein (BMP)-2] with MBD in postmenopausal women. We used NanoString nCounter platform to quantify plasma growth factor gene expression and Volpara to evaluate volumetric MBD measures. We investigated the associations of growth factor gene expression with MBD using both multiple linear regression (fold change) and multinomial logistic regression models, adjusted for potential confounders. The mean age of the 368 women enrolled was 58 years (range, 50-64). In analyses using linear regression models, one unit increase in IGF-1 gene expression was associated with a 35% higher volumetric percent density (VPD, 1.35; 95% confidence interval (CI), 1.13-1.60; P = 0.001). There were suggestions that TGFβ1 gene expression was positively associated with VPD while BMP-2 gene expression was inversely associated with VPD, but these were not statistically significant. In analyses using multinomial logistic regression, TGFβ1 gene expression was 33% higher (OR = 1.33; 95% CI, 1.13-1.56; P = 0.0008) in women with extremely dense breasts than those with almost entirely fatty breasts. There were no associations between growth factor gene expression and dense volume or nondense volume. Our study provides insights into the associations of growth factors with MBD in postmenopausal women and requires confirmation in other study populations.Prevention relevanceMammographic breast density is a strong risk factor for breast cancer. Understanding its underlying biological mechanisms could have utility in breast cancer prevention.

Project description: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 (Padj). 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) (Padj= 0.021). For rs35539615, change in percent MD increased by 1.79% per minor allele (Padj= 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%.

Dataset Information

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

Publications

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

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