Nature Communications (Oct 2020)
Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk
- Weiva Sieh,
- Joseph H. Rothstein,
- Robert J. Klein,
- Stacey E. Alexeeff,
- Lori C. Sakoda,
- Eric Jorgenson,
- Russell B. McBride,
- Rebecca E. Graff,
- Valerie McGuire,
- Ninah Achacoso,
- Luana Acton,
- Rhea Y. Liang,
- Jafi A. Lipson,
- Daniel L. Rubin,
- Martin J. Yaffe,
- Douglas F. Easton,
- Catherine Schaefer,
- Neil Risch,
- Alice S. Whittemore,
- Laurel A. Habel
Affiliations
- Weiva Sieh
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai
- Joseph H. Rothstein
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai
- Robert J. Klein
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
- Stacey E. Alexeeff
- Division of Research, Kaiser Permanente Northern California
- Lori C. Sakoda
- Division of Research, Kaiser Permanente Northern California
- Eric Jorgenson
- Division of Research, Kaiser Permanente Northern California
- Russell B. McBride
- Department of Pathology, Icahn School of Medicine at Mount Sinai
- Rebecca E. Graff
- Department of Epidemiology and Biostatistics, University of California San Francisco
- Valerie McGuire
- Department of Epidemiology and Population Health, Stanford University School of Medicine
- Ninah Achacoso
- Division of Research, Kaiser Permanente Northern California
- Luana Acton
- Division of Research, Kaiser Permanente Northern California
- Rhea Y. Liang
- Department of Radiology, Stanford University School of Medicine
- Jafi A. Lipson
- Department of Radiology, Stanford University School of Medicine
- Daniel L. Rubin
- Department of Radiology, Stanford University School of Medicine
- Martin J. Yaffe
- Departments of Medical Biophysics and Medical Imaging, University of Toronto
- Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and Department of Oncology, University of Cambridge
- Catherine Schaefer
- Division of Research, Kaiser Permanente Northern California
- Neil Risch
- Division of Research, Kaiser Permanente Northern California
- Alice S. Whittemore
- Department of Epidemiology and Population Health, Stanford University School of Medicine
- Laurel A. Habel
- Division of Research, Kaiser Permanente Northern California
- DOI
- https://doi.org/10.1038/s41467-020-18883-x
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 11
Abstract
Mammographic density represents one the strongest predictors of breast cancer risk. Here the authors perform genome-wide association study meta-analysis of women screened with full-field digital mammography and identify 31 previously unreported loci associated with mammographic density phenotypes.
