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Mammographic density is associated with many other breast cancer risk factors including age, body mass index and reproductive factors such as parity and menopause. These relationships are discussed in more detail below.

1.1.4.5.1 Age

Density decreases with age (137-141). Adjustments are therefore necessary in order to counteract the negative confounding of age on the density-risk relationship (27, 104). If no adjustment is made for age, the effect of density on risk will be underestimated (142). This creates a contradiction between density, age and breast cancer risk, since age and density are positively associated with risk, but inversely associated with each other. To help to understand this inconsistency, one could consider the cumulative rate of ‘breast tissue aging’ (i.e. cumulative rate of exposure to hormones) rather than chronological age, as suggested in Pike’s model (143, 144). Risk from density might reflect the breast tissue response to lifetime exposure of reproductive hormones (such as oestrogen) and growth factors (such as insulin-like growth factor (IGF-I) or prolactin) which stimulate epithelial and stromal cell division in the breast (78, 145-149). According to Pike’s model, the rate of breast tissue aging is most rapid at the time of menarche, slows with each pregnancy, slows further in the perimenopausal period, and is lowest after the menopause. This implies that an earlier age at menarche, nulliparity, later age at first birth and later age at menopause will increase cumulative exposure to hormones. Later menarche, parity, earlier age at first birth and earlier age at menopause are suggested to decrease cumulative exposure to hormones (27, 143, 144). It has been hypothesised that the higher the cumulative exposure to hormones, the higher the density. Hormonal exposures in early life might therefore be the most important predictors in the development of density, since this stage in life sees the highest rates of breast tissue aging.

Furthermore, the density and breast cancer risk association can be seen in both younger and older women (27, 79, 104). However, one must bear in mind that density estimates in women younger than the screening age may not be fully applicable to general populations of women. Since these younger women do not undergo routine mammography, density measures taken from this age group may be skewed by the potentially symptomatic or high-risk populations of women examined.

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Figure 1.4: Pik e’s model showing rates of breast tissue aging with chronological age.

The rate of breast tissue aging is greatest after menarche, declines with successive pregnancies and in the perimenopausal period, and is lowest after the last menstrual period i.e. post-menopause. This model is used as a theory to explain the increasing incidence rate of breast cancer with increasing age . Derived from Boyd et al. (78) which uses data from Pik e et al. (143) and Rosner and Colditz (144).

1.1.4.5.2 Menarche

There is only a small amount of literature regarding the association between age at menarche and breast density, but according to Pike’s model, one would expect there to be a correlation between early menarche and both increased density and increased breast cancer risk. There is some evidence to suggest that density is higher in women with early menarche (150), but this is not always the case (138). On the other hand, breast cancer risk increases with earlier menarche, but the effects are only marginal (151).

1.1.4.5.3 Parity

Density reduces with a first full-term pregnancy (152, 153), and reduces even further with each subsequent pregnancy (81, 153). This is thought to be due to the lower levels of reproductive hormones circulating post-pregnancy. Lower density is therefore associated with parity (81, 138, 152, 153) and earlier age at first full-term birth (152, 153).

0 10 20 30 40 50 60 70 Age (years) Br e a st t is su e e x p o su re ra te First full-term birth Start of perimenopausal stage Menarche Last menstrual period 1.0 0.8 0.6 0.4 0.2 0.0

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1.1.4.5.4 Menopause

Density reductions occur over the menopause (140, 154). This effect is thought to reflect the decrease in circulating reproductive hormones and increase in breast tissue involution that occur at this stage of female reproduction (155). Density is also positively associated with age at menopause, with lower densities existing in women who begin menopause at an earlier age (154). The density and breast cancer risk association is not limited to a particular menopausal status, with both premenopausal and postmenopausal women seeing higher risk with increasing density (104).

1.1.4.5.5 Body Mass Index

As well as age, systemic adiposity (commonly measured as body mass index (BMI)) is one of the strongest confounders of density (138, 156). Percent density, whether measured as PDA or PDV, is negatively associated with BMI (88, 157-165); as women with higher BMI are more likely to have higher non-dense tissue and total breast tissue (157, 166, 167) which will lead to lower percentage estimates of density. Absolute dense area has a less consistent relationship with BMI (87, 157-160, 168, 169). DV, on the other hand, has shown positive associations with BMI (161-165). These relationships are further complicated by the fact that density and excessive postmenopausal BMI are both positively associated with risk of breast cancer (170- 173), but (percent) density reduces with increasing BMI (88, 157-165). Relationships involving (percent) density as a risk factor therefore require an adjustment for BMI, otherwise breast cancer risk will be underestimated (174).

Some studies have also suggested a protective effect of BMI on breast cancer risk in premenopausal women (172, 175, 176). However, others have argued that these contrary findings are a result of negative confounding by density (166, 169).

To understand the contradictory relationships between adiposity, density and breast cancer risk, it helps to first understand the biological mechanisms behind the positive effect of BMI on breast cancer risk in postmenopausal women. This can largely be explained by the high levels of oestrogen present in overweight or obese postmenopausal women, as a result of the aromatase enzyme converting androgens to oestrogen in peripheral adipose tissue. This process of aromatisation acts as the main source of oestrogen in postmenopausal women whose hormonal production in the ovaries has ceased (177). Elevated levels of oestrogen act as a risk factor by binding to oestrogen receptor (ER)-positive tumour cells and stimulating their growth and proliferation (177).

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1.1.4.5.6 Endogenous hormones

Circulating endogenous oestrogen levels have been shown to influence the growth of density (146, 147, 178), making density a potential mediator for the effects of reproductive hormones on breast cancer risk. It has been theorised that density is a reflection of the breast tissue response to lifetime hormone exposure, as outlined in Pike’s model (143, 144). According to this theory, variations in density would mirror different levels of cumulative hormonal stimulation. However, this relationship between systemic hormones and density might not be applicable to all women, since little to no association between density and blood serum oestrogen has been seen in postmenopausal women (179-181). Some studies have investigated the role of local environments surrounding density, suggesting that certain hormones produced locally at these sites, may be stimulating the proliferation of epithelial cells. Most evidence suggests that a relationship exists between circulating oestrogens and density in premenopausal women, but not in postmenopausal women, with local breast tissue perhaps acting as the main oestrogen source in postmenopausal women (180-182).

Other hormones that are known to influence density include IGF-I and prolactin. High levels of serum IGF-I in premenopausal women and prolactin in postmenopausal women have shown significantly positive associations with density (145, 183, 184). Recent evidence to support this suggests that the breast cancer risk associations of plasma prolactin and mammographic density are independent in premenopausal women (185). It has also been suggested that consideration of both density and endogenous hormones (such as prolactin, circulating testosterone and estrone sulphate) may add to current breast cancer risk prediction models (185, 186).

1.1.4.5.7 Exogenous hormones

Hormone replacement therapy (HRT) increases both risk of breast cancer (142, 187, 188) and density (189-194). Specifically, combined oestrogen and progesterone HRT has greater associations with density than oestrogen only HRT (192-194), and continuous use of combined HRT is also associated with higher density than cycled HRT use (191, 194). However, the effects of HRT are only short-term, with a decrease in density visible just 4 weeks after HRT cessation (195, 196) and a decrease in risk (to the level of a non-HRT user) is apparent within a few years of stopping treatment (197).

Whilst HRT increases both risk of breast cancer and density, selective oestrogen receptor modulators (SERMs) have been shown to decrease risk (198-202), and certain SERMs, such as tamoxifen, can also reduce density (203-206). A study from the International Breast Cancer Intervention Study-I (IBIS-I) found that visually-assessed density reductions of 10% or more after 12-18 months of tamoxifen treatment were associated with an approximately 63%

41 reduction in breast cancer risk (OR=0.37, 95% CI, 0.20 to 0.69), p=0.002) compared with placebo, whereas smaller reductions or increases in density on tamoxifen had the same association with risk as placebo (OR=1.13, 95% CI, 0.72 to 1.77), p=0.60) (19). This suggests that change in density could be used as a biomarker to measure the efficacy of tamoxifen for prevention. Aromatase inhibitors (AIs), such as anastrozole, can also be used to treat and prevent breast cancer (207, 208). However, the effect of AIs on density is less clear, and it is yet unknown whether change in density can also be used as a biomarker for response to treatment with these drugs.

1.1.4.5.8 Heritability

Family history and heritability can also influence mammographic density. Twin studies have shown a 60% correlation between Cumulus-assessed PDA in monozygotic twins compared with 30% in dizygotic twins (209), and findings suggest that heritability can explain around two thirds of the residual variance seen in Cumulus-assessed PDA (209).

There has also been interest in the links between women with BRCA1/2 mutations and density (210, 211). Weak evidence suggests that BRCA1/2 carriers have higher density that is lower in contrast and coarser than low-risk women without these genetic mutations (210). However, studies also show similar relative risks of developing breast cancer for high density relative to low density amongst carriers of the BRCA1/2 mutation and non-carriers (211), proposing no effect modification by genetic mutations.

In addition to this, a series of genome-wide association studies (GWAS) have so far identified at least 100 Single Nucleotide Polymorphisms (SNPs) that are thought to be associated with breast cancer susceptibility (212, 213). Each of these SNPs has been shown to slightly modify an individual woman’s risk, but together, they could provide a significant amount of information regarding a woman’s risk. Attention has therefore turned towards these SNPs and investigations are on-going to ascertain their effect on density (212, 214-220). Candidate SNPs suggested to have an association between both breast cancer risk and density include SNPs located within the

HSD17B1, CYP1B1 and COMT oestrogen-related genes (218, 220), rs6220 (IGF-1) (217), rs3817198 (LSP1) (214), rs13281615 (8q) (214) and rs10509168 (ZNF365) (216), but the

effects of these latter SNPs on density require validation. A particular SNP, rs10995190 (ZNF365), has shown significance in more than one study (215, 216), suggesting a promising locus for further genetic evaluation. However, not all studies report an association between density and those SNPs identified in GWAS (219), and some studies suggest that independent information can be gained from the two risk factors (221); hence the relationship between SNPs, density and breast cancer risk remains an active area of research.

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