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A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
- Middha, Pooja;
- Wang, Xiaoliang;
- Behrens, Sabine;
- Bolla, Manjeet K;
- Wang, Qin;
- Dennis, Joe;
- Michailidou, Kyriaki;
- Ahearn, Thomas U;
- Andrulis, Irene L;
- Anton-Culver, Hoda;
- Arndt, Volker;
- Aronson, Kristan J;
- Auer, Paul L;
- Augustinsson, Annelie;
- Baert, Thaïs;
- Freeman, Laura E Beane;
- Becher, Heiko;
- Beckmann, Matthias W;
- Benitez, Javier;
- Bojesen, Stig E;
- Brauch, Hiltrud;
- Brenner, Hermann;
- Brooks-Wilson, Angela;
- Campa, Daniele;
- Canzian, Federico;
- Carracedo, Angel;
- Castelao, Jose E;
- Chanock, Stephen J;
- Chenevix-Trench, Georgia;
- Cordina-Duverger, Emilie;
- Couch, Fergus J;
- Cox, Angela;
- Cross, Simon S;
- Czene, Kamila;
- Dossus, Laure;
- Dugué, Pierre-Antoine;
- Eliassen, A Heather;
- Eriksson, Mikael;
- Evans, D Gareth;
- Fasching, Peter A;
- Figueroa, Jonine D;
- Fletcher, Olivia;
- Flyger, Henrik;
- Gabrielson, Marike;
- Gago-Dominguez, Manuela;
- Giles, Graham G;
- González-Neira, Anna;
- Grassmann, Felix;
- Grundy, Anne;
- Guénel, Pascal;
- Haiman, Christopher A;
- Håkansson, Niclas;
- Hall, Per;
- Hamann, Ute;
- Hankinson, Susan E;
- Harkness, Elaine F;
- Holleczek, Bernd;
- Hoppe, Reiner;
- Hopper, John L;
- Houlston, Richard S;
- Howell, Anthony;
- Hunter, David J;
- Ingvar, Christian;
- Isaksson, Karolin;
- Jernström, Helena;
- John, Esther M;
- Jones, Michael E;
- Kaaks, Rudolf;
- Keeman, Renske;
- Kitahara, Cari M;
- Ko, Yon-Dschun;
- Koutros, Stella;
- Kurian, Allison W;
- Lacey, James V;
- Lambrechts, Diether;
- Larson, Nicole L;
- Larsson, Susanna;
- Le Marchand, Loic;
- Lejbkowicz, Flavio;
- Li, Shuai;
- Linet, Martha;
- Lissowska, Jolanta;
- Martinez, Maria Elena;
- Maurer, Tabea;
- Mulligan, Anna Marie;
- Mulot, Claire;
- Murphy, Rachel A;
- Newman, William G;
- Nielsen, Sune F;
- Nordestgaard, Børge G;
- Norman, Aaron;
- O’Brien, Katie M;
- Olson, Janet E;
- Patel, Alpa V;
- Prentice, Ross;
- Rees-Punia, Erika;
- Rennert, Gad;
- Rhenius, Valerie;
- Ruddy, Kathryn J;
- Sandler, Dale P;
- Scott, Christopher G;
- Shah, Mitul;
- Shu, Xiao-Ou;
- Smeets, Ann;
- Southey, Melissa C;
- Stone, Jennifer;
- Tamimi, Rulla M;
- Taylor, Jack A;
- Teras, Lauren R;
- Tomczyk, Katarzyna;
- Troester, Melissa A;
- Truong, Thérèse;
- Vachon, Celine M;
- Wang, Sophia S;
- Weinberg, Clarice R;
- Wildiers, Hans;
- Willett, Walter;
- Winham, Stacey J;
- Wolk, Alicja;
- Yang, Xiaohong R;
- Zamora, M Pilar;
- Zheng, Wei;
- Ziogas, Argyrios;
- Dunning, Alison M;
- Pharoah, Paul DP;
- García-Closas, Montserrat;
- Schmidt, Marjanka K;
- Kraft, Peter;
- Milne, Roger L;
- Lindström, Sara;
- Easton, Douglas F;
- Chang-Claude, Jenny
- et al.
Published Web Location
https://doi.org/10.1186/s13058-023-01691-8Abstract
Background
Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.Methods
Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.Results
Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94).Conclusions
Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
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