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Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density
Jennifer Stone1, Deborah J Thompson2, Isabel Dos Santos Silva3
1Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia, Australia.
Cancer Research
|April 12, 2015
Summary
Genetic variants influence mammographic density, a breast cancer risk factor. Researchers identified new genetic associations with breast density measures, linking them to breast cancer risk and improving understanding of underlying causes.
Area of Science:
- Genetics
- Oncology
- Radiology
Background:
- Mammographic density is a heritable predictor of breast cancer risk.
- Few genetic variants associated with mammographic density have been identified.
- Understanding these genetic links is crucial for predicting breast cancer risk.
Purpose of the Study:
- To identify common genetic variants associated with mammographic density measures.
- To explore the relationship between breast cancer susceptibility variants and mammographic density.
- To investigate if genetic associations with density align with breast cancer risk.
Main Methods:
- Utilized data from 10,727 women across two international consortia.
- Employed mixed linear modeling to assess associations between 77 breast cancer susceptibility variants and mammographic density.
- Adjusted analyses for study, age, and body mass index (BMI).
Main Results:
- Confirmed associations for known variants (rs10995190, rs2046210, rs3817198) with dense areas.
- Identified novel associations for variants (rs1432679, rs17817449, rs12710696, rs3757318) with absolute and percent dense areas.
- Found 18% of breast cancer susceptibility variants were linked to at least one mammographic density measure, with consistent trends for breast cancer risk.
Conclusions:
- Multiple genetic loci are associated with both breast cancer risk and mammographic density.
- These findings highlight the genetic overlap between mammographic density and breast cancer.
- Further research into these loci may reveal key etiological pathways in breast cancer prediction.
