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.

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

BAGLIETTO, LAURA;
2014-01-01

Abstract

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.
2014
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.; Shane Pankratz, V.; 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/817956
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