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3 results on '"Achacoso, Ninah"'

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

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., and Habel, Laurel A.

Subjects
631/208/205/2138, 45/43, article, 692/4028/67/1347, humanities, 3. Good health, 692/4028/67/2324
Abstract

Funder: U.S. Department of Health & Human Services | National Institutes of Health (NIH), 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.

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

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., and Habel, Laurel A.

Subjects
631/208/205/2138, 45/43, article, 692/4028/67/1347, humanities, 3. Good health, 692/4028/67/2324
Abstract

Funder: U.S. Department of Health & Human Services | National Institutes of Health (NIH), 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.

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

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, and Habel, Laurel A

Subjects
Adult, Aged, 80 and over, Breast Neoplasms, Mendelian Randomization Analysis, Middle Aged, Polymorphism, Single Nucleotide, 3. Good health, Humans, Female, Genetic Predisposition to Disease, Aged, Breast Density, Genome-Wide Association Study, Mammography
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.

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