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Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures

Authors :
Christopher A. Haiman
Robert Luben
Laurence N. Kolonel
Aditi Hazra
Loic Le Marchand
Peter Kraft
Douglas F. Easton
Christy G. Woolcott
Jennifer Stone
Kavitha Krishnan
Sara Lindström
Katharina Heusinger
Julie A. Douglas
Vessela N. Kristensen
Alison M. Dunning
Christopher G. Scott
Qin Wang
Fergus J. Couch
Giske Ursin
V. Shane Pankratz
Matthew B. Jensen
Laura Baglietto
Heang Ping Chan
Matthias W. Beckmann
Rulla M. Tamimi
Celine M. Vachon
Jacques Simard
Peter A. Fasching
Manjeet K. Bolla
Kamila Czene
Kay-Tee Khaw
John L. Hopper
Judith E. Brown
Grethe I. Grenaker Alnæs
Gertraud Maskarinec
Joe Dennis
Graham G. Giles
Jean Leyland
Jingmei Li
Carmel Apicella
Kaanan P. Shah
Louise Eriksson
Irene L. Andrulis
Melissa C. Southey
Paul D.P. Pharoah
Sebastian M. Jud
Per Hall
Inger T. Gram
Isabel dos Santos Silva
Janet E. Olson
Julia A. Knight
Anne Lise Børresen-Dale
Mark A. Helvie
Kristen S. Purrington
Deborah J. Thompson
Ruth Warren
Kyriaki Michailidou
Nicholas J. Wareham
Paula Smith
Julie M. Cunningham
Thompson, Deborah [0000-0003-1465-5799]
Luben, Robert [0000-0002-5088-6343]
Khaw, Kay-Tee [0000-0002-8802-2903]
Wareham, Nicholas [0000-0003-1422-2993]
Wang, Jean [0000-0002-9139-0627]
Dennis, Joe [0000-0003-4591-1214]
Pharoah, Paul [0000-0001-8494-732X]
Dunning, Alison [0000-0001-6651-7166]
Easton, Douglas [0000-0003-2444-3247]
Apollo - University of Cambridge Repository
Publication Year :
2015
Publisher :
American Association for Cancer Research (AACR), 2015.

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. Cancer Res; 75(12); 2457–67. ©2015 AACR.

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....de472091b6fb2c00b48fa87dbe91f9cc