| Literature DB >> 25862352 |
Jennifer Stone1, Deborah J Thompson2, Isabel Dos Santos Silva3, Christopher Scott4, Rulla M Tamimi5, Sara Lindstrom6, Peter Kraft7, Aditi Hazra8, Jingmei Li9, Louise Eriksson10, Kamila Czene10, Per Hall10, Matt Jensen4, Julie Cunningham11, Janet E Olson12, Kristen Purrington13, Fergus J Couch14, Judith Brown2, Jean Leyland2, Ruth M L Warren15, Robert N Luben16, Kay-Tee Khaw17, Paula Smith18, Nicholas J Wareham19, Sebastian M Jud20, Katharina Heusinger20, Matthias W Beckmann20, Julie A Douglas21, Kaanan P Shah21, Heang-Ping Chan22, Mark A Helvie22, Loic Le Marchand23, Laurence N Kolonel23, Christy Woolcott24, Gertraud Maskarinec23, Christopher Haiman25, Graham G Giles26, Laura Baglietto27, Kavitha Krishnan28, Melissa C Southey29, Carmel Apicella28, Irene L Andrulis30, Julia A Knight31, Giske Ursin32, Grethe I Grenaker Alnaes33, Vessela N Kristensen33, Anne-Lise Borresen-Dale33, Inger Torhild Gram34, Manjeet K Bolla2, Qin Wang34, Kyriaki Michailidou2, Joe Dennis2, Jacques Simard35, Paul Pharoah36, Alison M Dunning37, Douglas F Easton36, Peter A Fasching38, V Shane Pankratz4, John L Hopper28, Celine M Vachon39.
Abstract
Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. ©2015 American Association for Cancer Research.Entities:
Mesh：
Year: 2015 PMID： 25862352 PMCID： PMC4470785 DOI： 10.1158/0008-5472.CAN-14-2012
Source DB: PubMed Journal: Cancer Res ISSN： 0008-5472 Impact factor: 12.701