Interactions between genetic and epidemiological factors influencing mammographic density
Studies have identified genetic and epidemiological factors associated with mammographic density (MD) phenotypes. However, MD-associated genetic variants only account for a small proportion of the total estimated heritability. Interrogating interactions between genetic and epidemiological factors could potentially identify additional MD-associated loci, expand our understanding of the genetic basis of MD phenotypes, and clarify how epidemiological factors modulate relationships between genetic variants and MD. We conducted six separate genome-wide, gene-environment (GxE) interaction analyses, applying 2 degrees of freedom (df) and 1df interaction tests, for each of three MD phenotypes (percent density (PD), dense area (DA), and non-dense area (NDA)). The six epidemiological factors considered were height, ever parous, parity, ever menopausal hormone therapy (MHT), ever breastfeeding, and months of breastfeeding. We included European ancestry participants from multiple studies within the Markers of Density (MODE) consortium and the Breast Cancer Association Consortium (BCAC) (n = 4,895 - 16,218 depending on specific analyses). We identified 11 loci with genome-wide significant (P < 5 × 10-8) interaction tests including two novel common genetic signals interacting with parity (8p21.2) and ever breastfeeding (19p13.2) for NDA. Our results suggest that epidemiological risk factors might influence relationships between common genetic variants and MD phenotypes at particular genomic loci.
Authors
- A. Heather Eliassen (ORCID: https://orcid.org/0000-0002-3961-6609)
- Fergus J. Couch (ORCID: https://orcid.org/0000-0001-9417-9985)
- Peter A. Fasching (ORCID: https://orcid.org/0000-0003-4885-8471)
- William Tapper (ORCID: https://orcid.org/0000-0002-5896-1889)
- Aaron D. Norman (ORCID: https://orcid.org/0000-0002-4208-2708)
- Jose E. Castelao (ORCID: https://orcid.org/0000-0001-7110-1376)
- Manuela Gago-Domínguez (ORCID: https://orcid.org/0000-0001-6713-4351)
- John L. Hopper (ORCID: https://orcid.org/0000-0002-8567-173X)
- Sophia Wang (ORCID: https://orcid.org/0000-0003-2597-9393)
- Joe Dennis (ORCID: https://orcid.org/0000-0003-4591-1214)
- Tabitha A. Harrison (ORCID: https://orcid.org/0000-0002-4173-7530)
- Alison M. Dunning (ORCID: https://orcid.org/0000-0001-6651-7166)
- Cameron B. Haas (ORCID: https://orcid.org/0000-0002-8211-0806)
- Kamila Czene (ORCID: https://orcid.org/0000-0002-3233-5695)
- Roger Laughlin Milne (ORCID: https://orcid.org/0000-0001-5764-7268)
- Kyriaki Michailidou (ORCID: https://orcid.org/0000-0001-7065-1237)
- Rulla M. Tamimi (ORCID: https://orcid.org/0000-0003-2306-8668)
- Rachel A. Murphy (ORCID: https://orcid.org/0000-0003-4383-5641)
- Gretchen L. Gierach (ORCID: https://orcid.org/0000-0002-0165-5522)
- Amy Berrington de González (ORCID: https://orcid.org/0000-0002-7332-8387)
- Jennifer Stone (ORCID: https://orcid.org/0000-0001-5077-0124)
- Celine M. Vachon
- Shaoqi Fan (ORCID: https://orcid.org/0000-0001-5894-7510)
- Montserrat García‐Closas (ORCID: https://orcid.org/0000-0003-1033-2650)
- Siddhartha Yadav (ORCID: https://orcid.org/0000-0003-4630-9903)
- Christopher G. Scott (ORCID: https://orcid.org/0000-0003-1340-0647)
- D. Gareth Evans (ORCID: https://orcid.org/0000-0002-8482-5784)
- Kristan J. Aronson (ORCID: https://orcid.org/0000-0002-7865-7243)
- Hongjie Chen (ORCID: https://orcid.org/0000-0002-6438-108X)
- Austin Hammermeister Suger (ORCID: https://orcid.org/0000-0002-6599-2202)
- Paul D P Pharoah
- Antonis C Antoniou
- Douglas F. Easton
- Sara Lindström
- Per Hall
- Manjeet K. Bolla (ORCID: https://orcid.org/0000-0002-4351-9326)
- Lothar Haeberle
- Susan Astley (ORCID: https://orcid.org/0000-0002-2989-2765)
- Diana Eccles (ORCID: https://orcid.org/0000-0002-9935-3169)
Institutions
- Cedars-Sinai Medical Center (US)
- Brigham and Women's Hospital (US)
- BC Cancer Agency (CA)
- Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa (ZA)
- Mayo Clinic (US)
- Harvard University (US)
- University of British Columbia (CA)
- Institute of Cancer Research (GB)
- The University of Melbourne (AU)
- The University of Western Australia (AU)
- Cancer Council Victoria (AU)
- University of Washington (US)
- Queen's University (CA)
- Cornell University (US)
- University of Cambridge (GB)
- Manchester Academic Health Science Centre (GB)
- Karolinska Institutet (SE)
- University of Manchester (GB)
- Universitätsklinikum Erlangen (DE)
- Fred Hutch Cancer Center (US)
- Manchester University NHS Foundation Trust (GB)
- Complejo Hospitalario Universitario de Santiago (ES)
- Bridge University (SS)
- St Mary's Hospital (GB)
- Monash Health (AU)
- National Cancer Institute (UA)
- Fundación Pública Galega de Medicina Xenómica (ES)
- National Cancer Institute (US)
- Cancer Genetics (United States) (US)
- Mayo Clinic in Florida (US)
- Instituto de Investigación Sanitaria de Santiago (ES)
- Comprehensive Cancer Center Erlangen (DE)
- Servicio Gallego de Salud (ES)
- MRC Epidemiology Unit (GB)
- University of Southampton (GB)
- Imperial College London (GB)
- Cyprus Institute of Neurology and Genetics (CY)
- Monash University (AU)
Publication Details
- Journal
- American Journal of Epidemiology
- Published
- 2025-03-27
- DOI
- https://doi.org/10.1093/aje/kwaf067
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00