Can genes for mammographic density inform cancer aetiology?
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ABSTRACT:
SUBMITTER: Kelemen LE
PROVIDER: S-EPMC2818036 | biostudies-literature | 2008 Oct
REPOSITORIES: biostudies-literature
Publications
Can genes for mammographic density inform cancer aetiology?
Kelemen Linda E LE Sellers Thomas A TA Vachon Celine M CM
Nature reviews. Cancer 20080905 10
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 dir ...[more]
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Project description:<p>We recruited 1,521 women from the Old Order Amish (OOA) population of Lancaster County, Pennsylvania, with the primary goal of identifying genetic factors that influence mammographic density. All women were between the ages of 40 and 88 years, with a mean of 54 years. Additional study design details, including eligibility criteria, are described elsewhere (Douglas et al., <a href="http://www.ncbi.nlm.nih.gov/pubmed/?term=19029399">2008</a>).</p> <p>The present-day OOA of Lancaster County are the descendants of approximately 550 individuals from central Western Europe who immigrated to the U.S. in the early eighteenth century. All living individuals derive from a single, 14-generation pedigree (Lee et al., <a href="http://www.ncbi.nlm.nih.gov/pubmed/?term=20433770">2010</a>). Although the OOA are a genetically closed founder population, allele frequencies and LD profiles are remarkably similar between the OOA and U.S. participants in the International HapMap project (HapMap CEU) for common SNPs (MAF>/=5%) (Van Hout et al., <a href="http://www.ncbi.nlm.nih.gov/pubmed?cmd=DetailsSearch&term=19697356[PMID]">2010</a>).</p> <p>We recently completed genome-wide linkage and association analyses of mammographic density, including dense and non-dense areas of the breast and the ratio of dense to total area of the breast. Summary-level data from our GWAS are available here and through the Marker of DEnsity (MODE) Consortium.</p>
| phs000604.v1.p1 | EGA
Project description:Recently, the Breast Cancer Association Consortium (BCAC) conducted a multi-stage genome-wide association study and identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer risk. Given the high degree of heritability of mammographic density and its strong association with breast cancer, it was hypothesised that breast cancer susceptibility loci may also be associated with breast density and provide insight into the biology of breast density and how it influences breast cancer risk.We conducted an analysis in the Nurses' Health Study (n = 1121) to assess the relation between 11 breast cancer susceptibility loci and mammographic density. At the time of their mammogram, 217 women were premenopausal and 904 women were postmenopausal. We used generalised linear models adjusted for covariates to determine the mean percentage of breast density according to genotype.Overall, no association between the 11 breast cancer susceptibility loci and mammographic density was seen. Among the premenopausal women, three SNPs (rs12443621 [TNRc9/LOC643714], rs3817198 [lymphocyte-specific protein-1] and rs4666451) were marginally associated with mammographic density (p < 0.10). All three of these SNPs showed an association that was consistent with the direction in which these alleles influence breast cancer risk. The difference in mean percentage mammographic density comparing homozygous wildtypes to homozygous variants ranged from 6.3 to 8.0%. None of the 11 breast cancer loci were associated with postmenopausal breast density.Overall, breast cancer susceptibility loci identified through a genome-wide association study do not appear to be associated with breast cancer risk.
| S-EPMC2575539 | biostudies-literature
Project description: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.
| S-EPMC4197055 | biostudies-literature
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| S-EPMC3000407 | biostudies-literature
Project description:Insulin-like growth factor-I (IGF-I) has mitogenic properties and stimulates cell growth. In this analysis, we investigated the relation between common genetic variation in IGF1, IGFBP1, and IGFBP3, and mammographic density among 819 women of Hawaiian, European, and Japanese ancestry from the Multiethnic Cohort Study. Mammographic density was assessed using a quantitative computer-assisted method. Previously identified tag single nucleotide polymorphisms (SNPs) for IGF1 (26 tag SNPs) and IGFBP1/IGFBP3 (22 tag SNPs) were genotyped among the 819 women. Mixed models were conducted to evaluate the associations between genetic variation and mammographic density. Two SNPs were borderline statistical significantly associated with mammographic density: rs35539615 on IGFBP1 (p = 0.05) and rs2453839 on IGFBP3 (p = 0.01). Rs35767on IGF1 (p = 0.03) was also associated with mammographic density, although in opposite direction of what was expected from previous findings with IGF-I levels. The majority of SNPs were, however, not associated with mammographic density. Analyses stratified by ethnicity showed similar results as the overall analyses for IGF1 and IGFBP1. However, for 4 SNPs in the IGFBP3 gene, the minor allele was associated with lower mammographic density in Japanese Americans and higher mammographic density in Caucasians. Given the large number of SNPs tested and the few borderline significant results, we only found weak evidence that genetic variations in IGFBP1 or IGFBP3 may be related to mammographic density. Ethnicity may modify these relations.
| S-EPMC2925500 | biostudies-literature
Project description:Mammographic density is one of the strongest predictors of breast cancer risk. Recently, it has been suggested that reactive oxygen species may influence breast cancer risk through its influence on mammographic density. In the current study, we addressed this hypothesis and also assessed if the association between carotenoids and breast cancer risk varies by mammographic density. We conducted a nested case-control study consisting of 604 breast cancer cases and 626 controls with prospectively measured circulating carotenoid levels and mammographic density in the Nurses' Health Study. Circulating levels of alpha-carotene, beta-carotene, beta-cryptoxanthin, lycopene, and lutein/zeaxanthin were measured. We used a computer-assisted thresholding method to measure percent mammographic density. We found no evidence that circulating carotenoids are inversely associated with mammographic density. However, mammographic density significantly modified the association between total circulating carotenoids and breast cancer (P heterogeneity = 0.008). Overall, circulating total carotenoids were inversely associated with breast cancer risk (P trend = 0.01). Among women in the highest tertile of mammographic density, total carotenoids were associated with a 50% reduction in breast cancer risk (odds ratio, 0.5; 95% confidence interval, 0.3-0.8). In contrast, there was no inverse association between carotenoids and breast cancer risk among women with low mammographic density. Similarly, among women in the highest tertile of mammographic density, high levels of circulating alpha-carotene, beta-cryptoxanthin, lycopene, and lutein/zeaxanthin were associated with a significant 40% to 50% reduction in breast cancer risk (P trend < 0.05). Our results suggest that plasma levels of carotenoids may play a role in reducing breast cancer risk, particularly among women with high mammographic density.
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Project description:BACKGROUND:Mammographic density is a strong risk factor for breast cancer. METHODS:We present a novel approach to enhance area density measures that takes advantage of the relative density of the pectoral muscle that appears in lateral mammographic views. We hypothesized that the grey scale of film mammograms is normalized to volume breast density but not pectoral density and thus pectoral density becomes an independent marker of volumetric density. RESULTS:From analysis of data from a Swedish case-control study (1,286 breast cancer cases and 1,391 control subjects, ages 50-75 years), we found that the mean intensity of the pectoral muscle (MIP) was highly associated with breast cancer risk [per SD: OR = 0.82; 95% confidence interval (CI), 0.75-0.88; P = 6 × 10(-7)] after adjusting for a validated computer-assisted measure of percent density (PD), Cumulus. The area under curve (AUC) changed from 0.600 to 0.618 due to using PD with the pectoral muscle as reference instead of a standard area-based PD measure. We showed that MIP is associated with a genetic variant known to be associated with mammographic density and breast cancer risk, rs10995190, in a subset of women with genetic data. We further replicated the association between MIP and rs10995190 in an additional cohort of 2,655 breast cancer cases (combined P = 0.0002). CONCLUSIONS:MIP is a marker of volumetric density that can be used to complement area PD in mammographic density studies and breast cancer risk assessment. IMPACT:Inclusion of MIP in risk models should be considered for studies using area PD from analog films.
| S-EPMC5085828 | biostudies-literature
Project description:BackgroundMammographic density (MD) is a strong risk factor for breast cancer. We examined how breast cancer risk factors are associated with MD area (cm2) change across age.MethodsWe conducted a cohort study of 31 782 Swedish women ages 40-70 years at time of baseline mammogram. Lifestyle and reproductive risk factors were assessed by a web-based questionnaire. MD was measured as dense area using the STRATUS method (mean over the left and right breast). Linear regression analyses with adjustments for age, body mass index (BMI), and menopausal status at baseline were performed to assess the association between breast cancer risk factors and mean baseline MD. To investigate mean MD change across age, linear regression analyses with adjustments for age, BMI, menopausal status, and age at last mammogram were performed. All tests of statistical significance were two-sided.ResultsExcept for oral contraceptive use, established lifestyle and reproductive risk factors for breast cancer were associated with baseline mean MD. The overall average annual MD change was -1.0 cm2. BMI and physical activity were statistically significantly associated with MD change. Lean women (BMI <20 kg/m2) had a mean MD change of -1.13 cm2 per year (95% confidence interval = -1.25 to -1.02) compared with -0.46 cm2 per year (95% confidence interval = -0.57 to -0.35) for women with BMI 30 or higher. The annual MD change was -0.4 cm2 larger in women who were very physically active compared with less physically active women.ConclusionsOur results indicate that all risk factors for breast cancer, except oral contraceptive use, are associated with baseline MD but that only age, BMI, and physical activity are determinants of MD change.
| S-EPMC6649843 | biostudies-literature
Project description:Percent mammographic density (PMD) is a strong breast cancer risk factor, however, other mammographic features, such as V, the standard deviation (SD) of pixel intensity, may be associated with risk. We assessed whether PMD, automated PMD (APD), and V, yielded independent associations with breast cancer risk. We included 1900 breast cancer cases and 3921 matched controls from the Nurses' Health Study (NHS) and the NHSII. Using digitized film mammograms, we estimated PMD using a computer-assisted thresholding technique. APD and V were determined using an automated computer algorithm. We used logistic regression to generate odds ratios (ORs) and 95% confidence intervals (CIs). Median time from mammogram to diagnosis was 4.1 years (interquartile range: 1.6-6.8 years). PMD (OR per SD:1.52, 95% CI: 1.42, 1.63), APD (OR per SD:1.32, 95% CI: 1.24, 1.41), and V (OR per SD:1.32, 95% CI: 1.24, 1.40) were positively associated with breast cancer risk. Associations for APD were attenuated but remained statistically significant after mutual adjustment for PMD or V. Women in the highest quartile of both APD and V (OR vs Q1/Q1: 2.49, 95% CI: 2.02, 3.06), or PMD and V (OR vs Q1/Q1: 3.57, 95% CI: 2.79, 4.58) had increased breast cancer risk. An automated method of PMD assessment is feasible and yields similar, but somewhat weaker, estimates to a manual measure. PMD, APD and V are each independently, positively associated with breast cancer risk. Women with dense breasts and greater texture variation are at the highest relative risk of breast cancer.
| S-EPMC8166859 | biostudies-literature
Project description:BackgroundMammographic density (MD) is a strong risk factor for breast cancer. We examined how endogenous plasma hormones are associated with average MD area (cm2) and annual MD change (cm2/year).MethodsThis study within the prospective KARMA cohort included analyses of plasma hormones of 1040 women. Hormones from the progestogen (n = 3), androgen (n = 7), oestrogen (n = 2) and corticoid (n = 5) pathways were analysed by ultra-performance supercritical fluid chromatography-tandem mass spectrometry (UPSFC-MS/MS), as well as peptide hormones and proteins (n = 2). MD was measured as a dense area using the STRATUS method (mean over the left and right breasts) and mean annual MD change over time.ResultsGreater baseline mean MD was associated with overall higher concentrations of progesterone (average + 1.29 cm2 per doubling of hormone concentration), 17OH-progesterone (+ 1.09 cm2), oesterone sulphate (+ 1.42 cm2), prolactin (+ 2.11 cm2) and SHBG (+ 4.18 cm2), and inversely associated with 11-deoxycortisol (- 1.33 cm2). The association between MD and progesterone was confined to the premenopausal women only. The overall annual MD change was - 0.8 cm2. Hormones from the androgen pathway were statistically significantly associated with MD change. The annual MD change was - 0.96 cm2 and - 1.16 cm2 lesser, for women in the highest quartile concentrations of testosterone and free testosterone, respectively, compared to those with the lowest concentrations.ConclusionsOur results suggest that, whereas hormones from the progestogen, oestrogen and corticoid pathways drive baseline MD, MD change over time is mainly driven by androgens. This study emphasises the complexity of risk factors for breast cancer and their mechanisms of action.
| S-EPMC7449090 | biostudies-literature