Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants
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Author
Mavaddat, Nasim
Pharoah, Paul D. P.
Michailidou, Kyriaki
Tyrer, Jonathan
Brook, Mark N.
Bolla, Manjeet K.
Wang, Qin
Dennis, Joe
Dunning, Alison M.
Shah, Mitul
Luben, Robert
Brown, Judith
Bojesen, Stig E.
Nordestgaard, Børge G.
Nielsen, Sune F.
Flyger, Henrik
Czene, Kamila
Darabi, Hatef
Eriksson, Mikael
Peto, Julian
dos-Santos-Silva, Isabel
Dudbridge, Frank
Johnson, Nichola
Schmidt, Marjanka K.
Broeks, Annegien
Verhoef, Senno
Rutgers, Emiel J.
Swerdlow, Anthony
Ashworth, Alan
Orr, Nick
Schoemaker, Minouk J.
Figueroa, Jonine
Chanock, Stephen J.
Brinton, Louise
Lissowska, Jolanta
Couch, Fergus J.
Olson, Janet E.
Vachon, Celine
Pankratz, Vernon S.
Lambrechts, Diether
Wildiers, Hans
Van Ongeval, Chantal
van Limbergen, Erik
Kristensen, Vessela
Grenaker Alnæs, Grethe
Nord, Silje
Borresen-Dale, Anne-Lise
Nevanlinna, Heli
Muranen, Taru A.
Aittomäki, Kristiina
Blomqvist, Carl
Chang-Claude, Jenny
Rudolph, Anja
Seibold, Petra
Flesch-Janys, Dieter
Fasching, Peter A.
Haeberle, Lothar
Ekici, Arif B.
Beckmann, Matthias W.
Burwinkel, Barbara
Marme, Frederik
Schneeweiss, Andreas
Sohn, Christof
Trentham-Dietz, Amy
Newcomb, Polly
Titus, Linda
Egan, Kathleen M.
Lindstrom, Sara
Rahman, Nazneen
Turnbull, Clare
Renwick, Anthony
Seal, Sheila
Li, Jingmei
Liu, Jianjun
Humphreys, Keith
Benitez, Javier
Pilar Zamora, M.
Arias Perez, Jose Ignacio
Menéndez, Primitiva
Jakubowska, Anna
Lubinski, Jan
Jaworska-Bieniek, Katarzyna
Durda, Katarzyna
Bogdanova, Natalia V.
Antonenkova, Natalia N.
Dörk, Thilo
Anton-Culver, Hoda
Neuhausen, Susan L.
Ziogas, Argyrios
Bernstein, Leslie
Devilee, Peter
Tollenaar, Robert A. E. M.
Seynaeve, Caroline
van Asperen, Christi J.
Cox, Angela
Cross, Simon S.
Reed, Malcolm W. R.
Khusnutdinova, Elza
Bermisheva, Marina
Prokofyeva, Darya
Takhirova, Zalina
Meindl, Alfons
Schmutzler, Rita K.
Sutter, Christian
Yang, Rongxi
Schürmann, Peter
Bremer, Michael
Christiansen, Hans
Park-Simon, Tjoung-Won
Hillemanns, Peter
Guénel, Pascal
Truong, Thérèse
Menegaux, Florence
Sanchez, Marie
Radice, Paolo
Peterlongo, Paolo
Manoukian, Siranoush
Pensotti, Valeria
Hopper, John L.
Tsimiklis, Helen
Apicella, Carmel
Southey, Melissa C.
Brauch, Hiltrud
Brüning, Thomas
Ko, Yon-Dschun
Sigurdson, Alice J.
Doody, Michele M.
Hamann, Ute
Torres, Diana
Ulmer, Hans-Ulrich
Försti, Asta
Sawyer, Elinor J.
Tomlinson, Ian
Kerin, Michael J.
Miller, Nicola
Andrulis, Irene L.
Knight, Julia A.
Glendon, Gord
Marie Mulligan, Anna
Chenevix-Trench, Georgia
Balleine, Rosemary
Giles, Graham G.
Milne, Roger L.
McLean, Catriona
Lindblom, Annika
Margolin, Sara
Haiman, Christopher A.
Henderson, Brian E.
Schumacher, Fredrick
Le Marchand, Loic
Eilber, Ursula
Wang-Gohrke, Shan
Hooning, Maartje J.
Hollestelle, Antoinette
van den Ouweland, Ans M. W.
Koppert, Linetta B.
Carpenter, Jane
Clarke, Christine
Scott, Rodney
Mannermaa, Arto
Kataja, Vesa
Kosma, Veli-Matti
Hartikainen, Jaana M.
Brenner, Hermann
Arndt, Volker
Stegmaier, Christa
Karina Dieffenbach, Aida
Winqvist, Robert
Pylkäs, Katri
Jukkola-Vuorinen, Arja
Grip, Mervi
Offit, Kenneth
Vijai, Joseph
Robson, Mark
Rau-Murthy, Rohini
Dwek, Miriam
Swann, Ruth
Annie Perkins, Katherine
Goldberg, Mark S.
Labrèche, France
Dumont, Martine
Eccles, Diana M.
Tapper, William J.
Rafiq, Sajjad
John, Esther M.
Whittemore, Alice S.
Slager, Susan
Yannoukakos, Drakoulis
Toland, Amanda E.
Yao, Song
Zheng, Wei
Halverson, Sandra L.
González-Neira, Anna
Pita, Guillermo
Rosario Alonso, M.
Álvarez, Nuria
Herrero, Daniel
Tessier, Daniel C.
Vincent, Daniel
Bacot, Francois
Luccarini, Craig
Baynes, Caroline
Ahmed, Shahana
Maranian, Mel
Healey, Catherine S.
Simard, Jacques
Hall, Per
Easton, Douglas F.
Garcia-Closas, Montserrat
Note: Order does not necessarily reflect citation order of authors.
Published Version
https://doi.org/10.1093/jnci/djv036Metadata
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Mavaddat, N., P. D. P. Pharoah, K. Michailidou, J. Tyrer, M. N. Brook, M. K. Bolla, Q. Wang, et al. 2015. “Prediction of Breast Cancer Risk Based on Profiling With Common Genetic Variants.” JNCI Journal of the National Cancer Institute 107 (5): djv036. doi:10.1093/jnci/djv036. http://dx.doi.org/10.1093/jnci/djv036.Abstract
Background: Data for multiple common susceptibility alleles for breast cancer may be combined to identify women at different levels of breast cancer risk. Such stratification could guide preventive and screening strategies. However, empirical evidence for genetic risk stratification is lacking. Methods: We investigated the value of using 77 breast cancer-associated single nucleotide polymorphisms (SNPs) for risk stratification, in a study of 33 673 breast cancer cases and 33 381 control women of European origin. We tested all possible pair-wise multiplicative interactions and constructed a 77-SNP polygenic risk score (PRS) for breast cancer overall and by estrogen receptor (ER) status. Absolute risks of breast cancer by PRS were derived from relative risk estimates and UK incidence and mortality rates. Results: There was no strong evidence for departure from a multiplicative model for any SNP pair. Women in the highest 1% of the PRS had a three-fold increased risk of developing breast cancer compared with women in the middle quintile (odds ratio [OR] = 3.36, 95% confidence interval [CI] = 2.95 to 3.83). The ORs for ER-positive and ER-negative disease were 3.73 (95% CI = 3.24 to 4.30) and 2.80 (95% CI = 2.26 to 3.46), respectively. Lifetime risk of breast cancer for women in the lowest and highest quintiles of the PRS were 5.2% and 16.6% for a woman without family history, and 8.6% and 24.4% for a woman with a first-degree family history of breast cancer. Conclusions: The PRS stratifies breast cancer risk in women both with and without a family history of breast cancer. The observed level of risk discrimination could inform targeted screening and prevention strategies. Further discrimination may be achievable through combining the PRS with lifestyle/environmental factors, although these were not considered in this report.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4754625/pdf/Terms of Use
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