Abstract
BackgroundPercent mammographic density (PD) estimates the proportion of stromal, fat, and epithelial breast tissues on the mammogram image. Adjusted for age and body mass index (BMI), PD is one of the strongest risk factors for breast cancer [1]. Inherited factors are hypothesized to explain between 30 and 60% of the variance in this trait [2–5]. However, previously identified common genetic variants account for less than 6% of the variance in PD, leaving much of the genetic contribution to this trait unexplained. We performed the first study to examine whether germline copy number variation (CNV) are associated with PD. Two genome-wide association studies (GWAS) of percent density conducted on the Illumina 660W-Quad were used to identify and replicate the association between candidate CNVs and PD: the Minnesota Breast Cancer Family Study (MBCFS) and controls from the Mayo Venous Thromboembolism (Mayo VTE) Case–Control Study, with 585 and 328 women, respectively. Linear models were utilized to examine the association of each probe with PD, adjusted for age, menopausal status and BMI. Segmentation was subsequently performed on the probe-level test statistics to identify candidate CNV regions that were associated with PD.ResultsSixty-one probes from five chromosomal regions [3q26.1 (2 regions), 8q24.22, 11p15.3, and 17q22] were significantly associated with PD in MBCFS (p-values <0.0001). A CNV at 3q26.1 showed the greatest evidence for association with PD; a region without any known SNPs. Conversely, the CNV at 17q22 was largely due to the association between SNPs and PD in the region. SNPs in the 8q24.22 region have been shown to be associated with risk of many cancers; however, SNPs in this region were not responsible for the observed CNV association. While we were unable to replicate the associations with PD, two of the five CNVs (3q26.1 and 11p15.3) were also observed in the Mayo VTE controls.ConclusionsCNVs may help to explain some of the variability in PD that is currently unexplained by SNPs. While we were able to replicate the existence of two CNVs across the two GWAS studies, we were unable to replicate the associations with PD. Even so, the proximity of the identified CNV regions to loci known to be associated with breast cancer risk suggests further investigation and potentially shared genetic mechanisms underlying the PD and breast cancer association.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1212-y) contains supplementary material, which is available to authorized users.
Highlights
Percent mammographic density (PD) estimates the proportion of stromal, fat, and epithelial breast tis‐ sues on the mammogram image
PD was lower in the Mayo venous thromboembolism Case–Control Study (VTE) population, partly due to the slightly older age and higher body mass index (BMI), and due to drift in the PD measure can occur with time (Table 1)
The two 3q26.1 regions consisted of a total of 30 probes that were significantly associated with PD in Minnesota Breast Cancer Family Study (MBCFS) and were clustered in a region without single probe (SNP) on the Illumina 660W platform (Figure 1a)
Summary
Percent mammographic density (PD) estimates the proportion of stromal, fat, and epithelial breast tis‐ sues on the mammogram image. Atkinson et al BMC Res Notes (2015) 8:297 been identified to be associated with percent density using genome-wide association studies (GWAS), including a novel locus on chromosome 12q24 and established breast cancer loci, ZNF365, ESR1, LSP1 and RAD51L1, suggesting shared heritability between PD and breast cancer [6–8]. Together these SNPs are estimated to account for less than 6% of the variance in PD, leaving much of the genetic contribution to this trait unexplained. Several recent publications have linked germline copy number variation (CNV) in other regions of the genome, including both inter- and intra-genic regions, with risk or recurrence of breast cancer [21–24]
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