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Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk
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 ris...
| Autores principales: | , , , , , , , , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547012/ https://www.ncbi.nlm.nih.gov/pubmed/33037222 http://dx.doi.org/10.1038/s41467-020-18883-x |
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| author | 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. |
| author_facet | 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. |
| author_sort | Sieh, Weiva |
| collection | PubMed |
| description | 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. |
| format | Online Article Text |
| id | pubmed-7547012 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2020 |
| publisher | Nature Publishing Group UK |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-75470122020-10-19 Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk 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. Nat Commun Article 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. Nature Publishing Group UK 2020-10-09 /pmc/articles/PMC7547012/ /pubmed/33037222 http://dx.doi.org/10.1038/s41467-020-18883-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
| spellingShingle | Article 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. Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk |
| title | Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk |
| title_full | Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk |
| title_fullStr | Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk |
| title_full_unstemmed | Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk |
| title_short | Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk |
| title_sort | identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk |
| topic | Article |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547012/ https://www.ncbi.nlm.nih.gov/pubmed/33037222 http://dx.doi.org/10.1038/s41467-020-18883-x |
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