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DOI 10.1038/ncomms6303

Медицинская библиотека · Nature communications · 2014

Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk.

Lindström Sara, Thompson Deborah J, Paterson Andrew D, Li Jingmei, Gierach Gretchen L, Scott Christopher, Stone Jennifer, Douglas Julie A, dos-Santos-Silva Isabel, Fernandez-Navarro Pablo, Verghase Jajini, Smith Paula, Brown Judith, Luben Robert, Wareham Nicholas J, Loos Ruth J F, Heit John A, Pankratz V Shane, Norman Aaron, Goode Ellen L, Cunningham Julie M, deAndrade Mariza, Vierkant Robert A, Czene Kamila, Fasching Peter A, Baglietto Laura, Southey Melissa C, Giles Graham G, Shah Kaanan P, Chan Heang-Ping, Helvie Mark A, Beck Andrew H, Knoblauch Nicholas W, Hazra Aditi, Hunter David J, Kraft Peter, Pollan Marina, Figueroa Jonine D, Couch Fergus J, Hopper John L, Hall Per, Easton Douglas F, Boyd Norman F, Vachon Celine M, Tamimi Rulla M

СтатьяПоддержка NIH: внешняя программаResearch Support, N.I.H., IntramuralПоддержка исследования: вне правительства СШАПоддержка правительства СШАПеревод в очереди

Аннотация

Mammographic density reflects the amount of stromal and epithelial tissues in relation to adipose tissue in the breast and is a strong risk factor for breast cancer. Here we report the results from meta-analysis of genome-wide association studies (GWAS) of three mammographic density phenotypes: dense area, non-dense area and percent density in up to 7,916 women in stage 1 and an additional 10,379 women in stage 2. We identify genome-wide significant (P<5 × 10(-8)) loci for dense area (AREG, ESR1, ZNF365, LSP1/TNNT3, IGF1, TMEM184B and SGSM3/MKL1), non-dense area (8p11.23) and percent density (PRDM6, 8p11.23 and TMEM184B). Four of these regions are known breast cancer susceptibility loci, and four additional regions were found to be associated with breast cancer (P<0.05) in a large meta-analysis. These results provide further evidence of a shared genetic basis between mammographic density and breast cancer and illustrate the power of studying intermediate quantitative phenotypes to identify putative disease-susceptibility loci.

Для цитирования: Lindström Sara, Thompson Deborah J, Paterson Andrew D, Li Jingmei, Gierach Gretchen L, Scott Christopher, Stone Jennifer, Douglas Julie A, dos-Santos-Silva Isabel, Fernandez-Navarro Pablo, Verghase Jajini, Smith Paula, Brown Judith, Luben Robert, Wareham Nicholas J, Loos Ruth J F, Heit John A, Pankratz V Shane, Norman Aaron, Goode Ellen L, Cunningham Julie M, deAndrade Mariza, Vierkant Robert A, Czene Kamila, Fasching Peter A, Baglietto Laura, Southey Melissa C, Giles Graham G, Shah Kaanan P, Chan Heang-Ping, Helvie Mark A, Beck Andrew H, Knoblauch Nicholas W, Hazra Aditi, Hunter David J, Kraft Peter, Pollan Marina, Figueroa Jonine D, Couch Fergus J, Hopper John L, Hall Per, Easton Douglas F, Boyd Norman F, Vachon Celine M, Tamimi Rulla M. Genome-wide association study identifies multiple loci associated with both mammographic density and breast cancer risk.. Nature communications. 2014. DOI: 10.1038/ncomms6303.

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