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- Title
Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk.
- Authors
Sieh, Weiva; Rothstein, Joseph H.; Klein, Robert J.; Alexeeff, Stacey E.; Sakoda, Lori C.; Jorgenson, Eric; McBride, Russell B.; Graff, Rebecca E.; McGuire, Valerie; Achacoso, Ninah; Acton, Luana; Liang, Rhea Y.; Lipson, Jafi A.; Rubin, Daniel L.; Yaffe, Martin J.; Easton, Douglas F.; Schaefer, Catherine; Risch, Neil; Whittemore, Alice S.; Habel, Laurel A.
- Abstract
Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10−8, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk. 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.
- Subjects
BREAST cancer; DIGITAL mammography; LOCUS (Genetics); PHENOTYPES; DENSITY; IDENTIFICATION
- Publication
Nature Communications, 2020, Vol 11, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-020-18883-x