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The Genetic Epidemiology of Breast Density: A Strong and Heritable...
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The Genetic Epidemiology of Breast Density: A Strong and Heritable Breast Cancer Risk Factor

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Epidemiology and Prevention".

Deadline for manuscript submissions: closed (15 May 2022) | Viewed by 12168

Special Issue Editors

Prof. Jennifer L. Stone

E-Mail Website
Guest Editor
University of Western Australia
Interests: breast density; breast cancer; breast screening; mammographic imaging; breast imaging
Dr. Sara Lindstroem

E-Mail Website
Co-Guest Editor
Department of Epidemiology, University of Washington,98195 Seattle, Washington, USA
Interests: breast density; breast cancer; genetic epidemiology
Prof. Dr. Melissa Southey

E-Mail Website
Co-Guest Editor
Precision Medicine, Monash Health, Monash University, Clayton, MEL 3800, Australia
Interests: precision medicine; cancer genomics; cancer prevention; public health; biobanking

Special Issue Information

Dear Colleagues,

Mammographic breast density is one of the strongest predictors of breast cancer risk and is highly heritable. Women with extensive breast density for their age are at significantly higher risk of developing breast cancer, and it is estimated that around 60% of the large variation in mammographic breast density measures is explained by genetic factors. There is increasing evidence supporting the use of breast density as an intermediate phenotype to identify additional common genetic variants associated with breast cancer risk. However, the genetic factors associated with the determination of mammographic breast density are still largely unknown.

This Special Issue aims to summarize the current understanding of the genetic epidemiology of breast density including genetic factors and their functions, the joint effects of genetic and non-genetic factors, and the biology of breast density. This Special Issue will also include reports on how this knowledge can be used facilitate the clinical use of breast density measurements to improve breast cancer outcomes by impacting critical points such as early detection and primary prevention strategies.

Prof. Jennifer L. Stone
Prof. Sara Lindstroem
Prof. Melissa Southey
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • breast density
  • mammographic density
  • breast cancer
  • risk factor
  • genetic risk variants
  • genetic determinants
  • biology
  • gene expression
  • gene function
  • epigenetics
  • endophenotype
  • intermediate phenotype
  • risk prediction
  • gene–environment interactions
  • mendelian randomization

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Published Papers (4 papers)

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Research

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11 pages, 291 KiB  
Article
Genetic Aspects of Mammographic Density Measures Associated with Breast Cancer Risk
by Shuai Li, Tuong L. Nguyen, Tu Nguyen-Dumont, James G. Dowty, Gillian S. Dite, Zhoufeng Ye, Ho N. Trinh, Christopher F. Evans, Maxine Tan, Joohon Sung, Mark A. Jenkins, Graham G. Giles, John L. Hopper and Melissa C. Southey
Cancers 2022, 14(11), 2767; https://doi.org/10.3390/cancers14112767 - 2 Jun 2022
Cited by 8 | Viewed by 2435
Abstract
Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. [...] Read more.
Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05–0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the “white but not bright area” (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer. Full article
(This article belongs to the Special Issue The Genetic Epidemiology of Breast Density: A Strong and Heritable Breast Cancer Risk Factor)
10 pages, 251 KiB  
Article
Familial Aspects of Mammographic Density Measures Associated with Breast Cancer Risk
by Tuong L. Nguyen, Shuai Li, James G. Dowty, Gillian S. Dite, Zhoufeng Ye, Tu Nguyen-Dumont, Ho N. Trinh, Christopher F. Evans, Maxine Tan, Joohon Sung, Mark A. Jenkins, Graham G. Giles, Melissa C. Southey and John L. Hopper
Cancers 2022, 14(6), 1483; https://doi.org/10.3390/cancers14061483 - 14 Mar 2022
Cited by 5 | Viewed by 2384
Abstract
Cumulus, Cumulus-percent, Altocumulus, Cirrocumulus, and Cumulus-white are mammogram risk scores (MRSs) for breast cancer based on mammographic density defined in effect by different levels of pixel brightness and adjusted for age and body mass index. We measured these MRS from [...] Read more.
Cumulus, Cumulus-percent, Altocumulus, Cirrocumulus, and Cumulus-white are mammogram risk scores (MRSs) for breast cancer based on mammographic density defined in effect by different levels of pixel brightness and adjusted for age and body mass index. We measured these MRS from digitized film mammograms for 593 monozygotic (MZ) and 326 dizygotic (DZ) female twin pairs and 1592 of their sisters. We estimated the correlations in relatives (r) and the proportion of variance due to genetic factors (heritability) using the software FISHER and predicted the familial risk ratio (FRR) associated with each MRS. The ρ estimates ranged from: 0.41 to 0.60 (standard error [SE] 0.02) for MZ pairs, 0.16 to 0.26 (SE 0.05) for DZ pairs, and 0.19 to 0.29 (SE 0.02) for sister pairs (including pairs of a twin and her non-twin sister), respectively. Heritability estimates were 39% to 69% under the classic twin model and 36% to 56% when allowing for shared non-genetic factors specific to MZ pairs. The FRRs were 1.08 to 1.17. These MRSs are substantially familial, due mostly to genetic factors that explain one-quarter to one-half as much of the familial aggregation of breast cancer that is explained by the current best polygenic risk score. Full article
(This article belongs to the Special Issue The Genetic Epidemiology of Breast Density: A Strong and Heritable Breast Cancer Risk Factor)
11 pages, 540 KiB  
Article
Is Mammographic Breast Density an Endophenotype for Breast Cancer?
by Ellie Darcey, Nina McCarthy, Eric K. Moses, Christobel Saunders, Gemma Cadby and Jennifer Stone
Cancers 2021, 13(15), 3916; https://doi.org/10.3390/cancers13153916 - 3 Aug 2021
Cited by 5 | Viewed by 2143
Abstract
Mammographic breast density (MBD) is a strong and highly heritable predictor of breast cancer risk and a biomarker for the disease. This study systematically assesses MBD as an endophenotype for breast cancer—a quantitative trait that is heritable and genetically correlated with disease risk. [...] Read more.
Mammographic breast density (MBD) is a strong and highly heritable predictor of breast cancer risk and a biomarker for the disease. This study systematically assesses MBD as an endophenotype for breast cancer—a quantitative trait that is heritable and genetically correlated with disease risk. Using data from the family-based kConFab Study and the 1994/1995 cross-sectional Busselton Health Study, participants were divided into three status groups—cases, relatives of cases and controls. Participant’s mammograms were used to measure absolute dense area (DA) and percentage dense area (PDA). To address each endophenotype criterion, linear mixed models and heritability analysis were conducted. Both measures of MBD were significantly associated with breast cancer risk in two independent samples. These measures were also highly heritable. Meta-analyses of both studies showed that MBD measures were higher in cases compared to relatives (β = 0.48, 95% CI = 0.10, 0.86 and β = 0.41, 95% CI = 0.06, 0.78 for DA and PDA, respectively) and in relatives compared to controls (β = 0.16, 95% CI = −0.24, 0.56 and β = 0.16, 95% CI = −0.21, 0.53 for DA and PDA, respectively). This study formally demonstrates, for the first time, that MBD is an endophenotype for breast cancer. Full article
(This article belongs to the Special Issue The Genetic Epidemiology of Breast Density: A Strong and Heritable Breast Cancer Risk Factor)
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Review

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21 pages, 14972 KiB  
Review
Biological Mechanisms and Therapeutic Opportunities in Mammographic Density and Breast Cancer Risk
by Maddison Archer, Pallave Dasari, Andreas Evdokiou and Wendy V. Ingman
Cancers 2021, 13(21), 5391; https://doi.org/10.3390/cancers13215391 - 27 Oct 2021
Cited by 9 | Viewed by 4011
Abstract
Mammographic density is an important risk factor for breast cancer; women with extremely dense breasts have a four to six fold increased risk of breast cancer compared to women with mostly fatty breasts, when matched with age and body mass index. High mammographic [...] Read more.
Mammographic density is an important risk factor for breast cancer; women with extremely dense breasts have a four to six fold increased risk of breast cancer compared to women with mostly fatty breasts, when matched with age and body mass index. High mammographic density is characterised by high proportions of stroma, containing fibroblasts, collagen and immune cells that suggest a pro-tumour inflammatory microenvironment. However, the biological mechanisms that drive increased mammographic density and the associated increased risk of breast cancer are not yet understood. Inflammatory factors such as monocyte chemotactic protein 1, peroxidase enzymes, transforming growth factor beta, and tumour necrosis factor alpha have been implicated in breast development as well as breast cancer risk, and also influence functions of stromal fibroblasts. Here, the current knowledge and understanding of the underlying biological mechanisms that lead to high mammographic density and the associated increased risk of breast cancer are reviewed, with particular consideration to potential immune factors that may contribute to this process. Full article
(This article belongs to the Special Issue The Genetic Epidemiology of Breast Density: A Strong and Heritable Breast Cancer Risk Factor)
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