Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk

被引:30
|
作者
Sieh, Weiva [1 ,2 ]
Rothstein, Joseph H. [1 ,2 ]
Klein, Robert J. [2 ]
Alexeeff, Stacey E. [3 ]
Sakoda, Lori C. [3 ]
Jorgenson, Eric [3 ]
McBride, Russell B. [4 ]
Graff, Rebecca E. [5 ]
McGuire, Valerie [6 ]
Achacoso, Ninah [3 ]
Acton, Luana [3 ]
Liang, Rhea Y. [7 ]
Lipson, Jafi A. [7 ]
Rubin, Daniel L. [7 ,8 ,9 ]
Yaffe, Martin J. [10 ,11 ]
Easton, Douglas F. [12 ,13 ]
Schaefer, Catherine [3 ]
Risch, Neil [3 ,5 ,14 ]
Whittemore, Alice S. [6 ,8 ]
Habel, Laurel A. [3 ]
机构
[1] Icahn Sch Med Mt Sinai, Dept Populat Hlth Sci & Policy, New York, NY 10029 USA
[2] Icahn Sch Med Mt Sinai, Dept Genet & Genom Sci, New York, NY 10029 USA
[3] Kaiser Permanente Northern Calif, Div Res, Oakland, CA USA
[4] Icahn Sch Med Mt Sinai, Dept Pathol, New York, NY 10029 USA
[5] Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
[6] Stanford Univ, Sch Med, Dept Epidemiol & Populat Hlth, Stanford, CA 94305 USA
[7] Stanford Univ, Sch Med, Dept Radiol, Stanford, CA 94305 USA
[8] Stanford Univ, Sch Med, Dept Biomed Data Sci, Stanford, CA 94305 USA
[9] Stanford Univ, Sch Med, Dept Med, Stanford, CA 94305 USA
[10] Univ Toronto, Dept Med Biophys, Toronto, ON, Canada
[11] Univ Toronto, Dept Med Imaging, Toronto, ON, Canada
[12] Univ Cambridge, Ctr Canc Genet Epidemiol, Dept Publ Hlth & Primary Care, Cambridge, England
[13] Univ Cambridge, Dept Oncol, Cambridge, England
[14] Univ Calif San Francisco, Inst Human Genet, San Francisco, CA 94143 USA
基金
加拿大健康研究院; 欧盟地平线“2020”; 美国国家卫生研究院;
关键词
GENOME-WIDE ASSOCIATION; GENETIC EPIDEMIOLOGY RESEARCH; GENOTYPE IMPUTATION; INTEGRATIVE ANALYSIS; ADULT HEALTH; HERITABILITY; LANDSCAPE; BIOMARKER; VARIANTS; TISSUE;
D O I
10.1038/s41467-020-18883-x
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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<5x10(-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.
引用
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页数:11
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