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

doi:10.1038/s41467-020-18883-x

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

Research output: Contribution to journal › Article › peer-review

27 Scopus citations

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.

Original language	English (US)
Article number	5116
Journal	Nature communications
Volume	11
Issue number	1
DOIs	https://doi.org/10.1038/s41467-020-18883-x
State	Published - Dec 1 2020
Externally published	Yes

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

Access to Document

10.1038/s41467-020-18883-x

Cite this

Sieh, W., Rothstein, J. H., Klein, R. J., Alexeeff, S. E., Sakoda, L. C., Jorgenson, E., McBride, R. B., Graff, R. E., McGuire, V., Achacoso, N., Acton, L., Liang, R. Y., Lipson, J. A., Rubin, D. L., Yaffe, M. J., Easton, D. F., Schaefer, C., Risch, N., Whittemore, A. S., & Habel, L. A. (2020). Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk. Nature communications, 11(1), Article 5116. https://doi.org/10.1038/s41467-020-18883-x

Sieh, W , Rothstein, JH, Klein, RJ, Alexeeff, SE, Sakoda, LC, Jorgenson, E, McBride, RB, Graff, RE, McGuire, V, Achacoso, N, Acton, L, Liang, RY, Lipson, JA, Rubin, DL, Yaffe, MJ, Easton, DF, Schaefer, C, Risch, N, Whittemore, AS & Habel, LA 2020, 'Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk', Nature communications, vol. 11, no. 1, 5116. https://doi.org/10.1038/s41467-020-18883-x

@article{a5ab16a67afe48ffa6de98700084bc7c,

title = "Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk",

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.",

author = "Weiva Sieh and Rothstein, {Joseph H.} and Klein, {Robert J.} and Alexeeff, {Stacey E.} and Sakoda, {Lori C.} and Eric Jorgenson and McBride, {Russell B.} and Graff, {Rebecca E.} and Valerie McGuire and Ninah Achacoso and Luana Acton and Liang, {Rhea Y.} and Lipson, {Jafi A.} and Rubin, {Daniel L.} and Yaffe, {Martin J.} and Easton, {Douglas F.} and Catherine Schaefer and Neil Risch and Whittemore, {Alice S.} and Habel, {Laurel A.}",

note = "Publisher Copyright: {\textcopyright} 2020, The Author(s).",

year = "2020",

month = dec,

day = "1",

doi = "10.1038/s41467-020-18883-x",

language = "English (US)",

volume = "11",

journal = "Nature communications",

issn = "2041-1723",

publisher = "Nature Publishing Group",

number = "1",

}

TY - JOUR

T1 - Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk

AU - Sieh, Weiva

AU - Rothstein, Joseph H.

AU - Klein, Robert J.

AU - Alexeeff, Stacey E.

AU - Sakoda, Lori C.

AU - Jorgenson, Eric

AU - McBride, Russell B.

AU - Graff, Rebecca E.

AU - McGuire, Valerie

AU - Achacoso, Ninah

AU - Acton, Luana

AU - Liang, Rhea Y.

AU - Lipson, Jafi A.

AU - Rubin, Daniel L.

AU - Yaffe, Martin J.

AU - Easton, Douglas F.

AU - Schaefer, Catherine

AU - Risch, Neil

AU - Whittemore, Alice S.

AU - Habel, Laurel A.

PY - 2020/12/1

Y1 - 2020/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85092309847&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85092309847&partnerID=8YFLogxK

U2 - 10.1038/s41467-020-18883-x

DO - 10.1038/s41467-020-18883-x

M3 - Article

C2 - 33037222

AN - SCOPUS:85092309847

SN - 2041-1723

VL - 11

JO - Nature communications

JF - Nature communications

IS - 1

M1 - 5116

ER -

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

Abstract

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this