With their unique cultural customs and relatively similar environmental exposures, a well-defined, genetically closed population structure, and extensive genealogical records, the OOA provide an ideal context in which to study the genetic contributions to breast density. Of particular relevance to studying breast density, the OOA population is characterized by a very low prevalence of exogenous hormone use, including oral contraceptives and HRT, and high parity. Still, our results suggest that breast density varies widely in the OOA population, with values that are comparable to other highly parous populations. For example, in a sample of 294 Hispanic women (2/3 of whom were post-menopausal and 3/4 of whom reported 3 or more live births), Lopez et al.(28
) reported an overall mean of 17.7% for percent breast density, with a range of 1.9–54.6%. Similarly, in our sample of women (~2/3 of whom were also post-menopausal and 3/4 of whom reported 5 or more live births), the mean and range of percent breast density were 15.8% and 1.4–59%, respectively.
To our knowledge, our study is the first non-twin study to estimate the genetic contributions to the dense and non-dense areas of the breast, and the first study to examine the contribution of genetic factors to the correlation between breast density and other breast cancer risk factors. We found that both the dense and non-dense areas of the breast were significantly heritable in our sample, with 33% and 68% of the total variance, respectively, attributable to additive genetic effects. Although these estimates are consistent with the significant genetic influences reported by Stone et al.(13
), comparisons of heritability are always ill-advised. For example, with respect to the environmental factors that impact breast density, the women in this sample likely share relatively similar environments. Thus, all one can infer from a relatively higher (or lower) estimate of heritability is that there is less (or more) environmental variation relative to the genetic variation in this sample. We note that screening and adjusting for other significant covariates (in addition to age and menopausal status) did not meaningfully alter our estimates of the heritability of absolute breast density. In fact, age at menarche and number of live births were the only other covariates significantly correlated with log-transformed dense area, and together they explained no more than an additional 8% of the variation in this trait. After including all four covariates in our model, the heritability of the dense area of the breast was 36% (versus 39% with adjustment for age and menopausal status only).
We also found that other breast cancer risk factors were significantly heritable and that some of their associations with breast density were due to an underlying structure of shared genetic (and environmental) effects. Particularly noteworthy is our finding that breast density and live birth number are genetically correlated. It has been commonly hypothesized that the inverse association between these two traits is due to a decrease in the proliferative activity of the parous epithelium, and in turn, that the subsequent decreased risk of breast cancer is due to the differentiation (during pregnancy) of lobular type 1 to 4 cells, which are assumed to be less susceptible to malignant transformation. Our results are consistent with this hypothesis and suggest that a significant component of this association may be due to genetic factors that influence breast density and live birth number (or fertility) in opposite directions. Because the OOA discourage the use of contraceptives and share a relatively uniform socio-cultural and -economic background, we were in a unique position to study this relationship. Of note, our finding of a significant genetic component to fertility is also consistent with a recent report by Pluzhnikov et al.(29
), who studied both components of reproductive fitness (fertility and mortality) in the Hutterites and found significant familial correlations in family size. At present, however, the genes that influence fertility in human populations are unknown, partly owing to the difficulty of controlling for the influence of non-genetic factors. Our results suggest it may be ill advised to adjust for live birth number in the genetic analysis of breast density given the strong genetic correlation between them.
Based on samples of unrelated women, Boyd et al.(10
) and Haars et al.(9
) previously showed that the inverse correlations of various measures of adiposity with breast density, expressed as a percentage of total breast area, are due to positive correlations with the non-dense area of the breast. Our data are consistent with these observations and suggest that many of these correlations may have a common and strong genetic basis. Specifically, in our sample, several measures of body size exhibited strong and significant positive genetic correlations with the non-dense (but not dense) area of the breast. For example, ~2/3 of the phenotypic correlation between the non-dense area of the breast and weight (0.77) was due to the same genetic factors after adjusting for age and menopausal status. As a result, any genetic analysis of percent breast density will be strongly confounded by adiposity. One such example is provided by Vachon et al., who recently reported that their linkage evidence on chromosome 5p for percent breast density nearly doubled after adjustment for BMI(15
). Although Vachon et al. recognized that percent breast density was genetically correlated with BMI in their sample (0.71), they were unable to analyze the dense and non-dense areas separately as only percent density was characterized.
In our sample, the non-dense area of the breast was also significantly (negatively) genetically correlated with age at menarche. Age at menarche was, in turn, significantly (negatively) genetically correlated with each of the adiposity measures described above (data not shown). Together, these correlations are consistent with findings from a recent study by Wang et al.(30
), who reported significant negative genetic correlations between several obesity phenotypes, including BMI and age at menarche. As described by Wang et al., these findings are biologically consistent with documented differences in hormonal concentrations and fat distribution in women who experience early versus late menarche.
In addition to identifying significant genetic correlations between the dense and non-dense areas of the breast and other breast cancer risk factors, we also found that the environmental correlations were significantly different from zero for several trait pairs. For example, the dense area of the breast was positively environmentally correlated with both age at menarche and height. These findings imply the existence of other important covariates that were either not included in our models, or more likely, not measured in our study, and are consistent with the individual-specific effects noted in our univariate analyses. For example, ~50% of the total variability in the dense area of the breast was unexplained by measured covariates and unmeasured additive genetic factors. Factors that may have contributed to this unexplained variation (and environmental correlation with other traits) include exposures that may have occurred earlier in life, e.g., dietary intake and hormones. Indeed, some of the hormonal factors that influence height also appear to regulate mammary gland development(31
Based on an analysis of MZ and DZ twins, Stone et al.(13
) previously reported a negative genetic correlation between the dense and non-dense areas of the breast (−0.30±0.04 (±standard error) after a logarithm transformation and adjustment for covariates). In our sample, however, the genetic correlation between these areas was positive (0.38±0.17 after transformation and adjustment for covariates). In other words, data from Stone et al. suggest that there exist common genetic influences that act in opposite directions on the dense and non-dense areas, while the data presented here suggest that these shared genetic influences operate in the same direction. It is interesting to note that the within-individual correlation between the dense and non-dense areas was also remarkably different between our two studies (after adjustment for age, 0.002 in our sample versus −0.35 in the sample of Stone et al.) but consistent with our study-specific environmental correlations, which were similar in sign and magnitude (−0.42±0.17 in our sample and −0.31±0.04 in their sample). Because our parameterizations, populations of inference, and study designs are not directly comparable, it is difficult to reconcile these differences.
Data from the present study add to the accumulating evidence that breast density has a strong heritable component and provide new evidence that part of this heritable component is shared with other breast cancer risk factors. Still, we acknowledge several study limitations. First, given our study design, we were unable to examine the influence of shared environments. For example, to the extent that shared childhood environments contribute to correlations in breast density between sisters, we may have overestimated the genetic contributions to individual differences in (and correlations between) breast density and other breast cancer risk factors. Second, our findings may not generalize to other populations, particularly given the unique reproductive practices of the OOA. In spite of this, our study participants were similar in many other ways to the U.S. female Caucasian population as determined by our analysis of age-matched data from the 2001–2002 National Health and Nutrition Examination Surveys (data not shown). Third, we were unable to examine (with confidence) the relationship between breast density and an important breast cancer risk factor, namely, family history of breast cancer. Irregular medical care practices in this population make it difficult to obtain and/or verify information on family cancer history. Fourth, with our modest sample size, we were underpowered to examine the extent to which genetic variances and correlations were menopausal specific. Tentative examination of menopausal-specific estimates of heritability and genetic and environmental correlations, however, suggests that the relative contributions of genetic and non-genetic factors were similar in pre- and post-menopausal women (data not shown).
In summary, our results indicate that breast density varies widely in the OOA population and is strongly influenced by genetic factors. Our results also suggest that the genetic and environmental factors that influence breast density are not independent of the genetic and environmental factors that influence other breast cancer risk factors. These findings are being used to inform our ongoing genetic investigation of breast density in the OOA. The evidence presented here for shared genetic influences on breast density and other breast cancer risk factors may lead to more powerful searches for the loci and genes that influence breast density. Indeed, the power to identify loci that influence breast density may be increased by jointly analyzing genetically correlated traits(32