TY - JOUR
T1 - A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
AU - CTS Consortium
AU - ABCTB Investigators
AU - kConFab Investigators
AU - Middha, Pooja
AU - Wang, Xiaoliang
AU - Behrens, Sabine
AU - Bolla, Manjeet K.
AU - Wang, Qin
AU - Dennis, Joe
AU - Michailidou, Kyriaki
AU - Ahearn, Thomas U.
AU - Andrulis, Irene L.
AU - Anton-Culver, Hoda
AU - Arndt, Volker
AU - Aronson, Kristan J.
AU - Auer, Paul L.
AU - Augustinsson, Annelie
AU - Baert, Thaïs
AU - Freeman, Laura E.Beane
AU - Becher, Heiko
AU - Beckmann, Matthias W.
AU - Benitez, Javier
AU - Bojesen, Stig E.
AU - Brauch, Hiltrud
AU - Brenner, Hermann
AU - Brooks-Wilson, Angela
AU - Campa, Daniele
AU - Canzian, Federico
AU - Carracedo, Angel
AU - Castelao, Jose E.
AU - Chanock, Stephen J.
AU - Chenevix-Trench, Georgia
AU - Cordina-Duverger, Emilie
AU - Couch, Fergus J.
AU - Cox, Angela
AU - Cross, Simon S.
AU - Czene, Kamila
AU - Dossus, Laure
AU - Dugué, Pierre Antoine
AU - Eliassen, A. Heather
AU - Eriksson, Mikael
AU - Evans, D. Gareth
AU - Fasching, Peter A.
AU - Figueroa, Jonine D.
AU - Fletcher, Olivia
AU - Flyger, Henrik
AU - Gabrielson, Marike
AU - Gago-Dominguez, Manuela
AU - Giles, Graham G.
AU - González-Neira, Anna
AU - Grassmann, Felix
AU - Grundy, Anne
AU - Guénel, Pascal
AU - Haiman, Christopher A.
AU - Håkansson, Niclas
AU - Hall, Per
AU - Hamann, Ute
AU - Hankinson, Susan E.
AU - Harkness, Elaine F.
AU - Holleczek, Bernd
AU - Hoppe, Reiner
AU - Hopper, John L.
AU - Houlston, Richard S.
AU - Howell, Anthony
AU - Hunter, David J.
AU - Ingvar, Christian
AU - Isaksson, Karolin
AU - Jernström, Helena
AU - John, Esther M.
AU - Jones, Michael E.
AU - Kaaks, Rudolf
AU - Keeman, Renske
AU - Kitahara, Cari M.
AU - Ko, Yon Dschun
AU - Koutros, Stella
AU - Kurian, Allison W.
AU - Lacey, James V.
AU - Lambrechts, Diether
AU - Larson, Nicole L.
AU - Larsson, Susanna
AU - Le Marchand, Loic
AU - Lejbkowicz, Flavio
AU - Li, Shuai
AU - Linet, Martha
AU - Lissowska, Jolanta
AU - Martinez, Maria Elena
AU - Maurer, Tabea
AU - Mulligan, Anna Marie
AU - Mulot, Claire
AU - Murphy, Rachel A.
AU - Newman, William G.
AU - Nielsen, Sune F.
AU - Nordestgaard, Børge G.
AU - Norman, Aaron
AU - O'Brien, Katie M.
AU - Olson, Janet E.
AU - Patel, Alpa V.
AU - Prentice, Ross
AU - Rees-Punia, Erika
AU - Rennert, Gad
AU - Rhenius, Valerie
AU - Ruddy, Kathryn J.
AU - Sandler, Dale P.
AU - Scott, Christopher G.
AU - Shah, Mitul
AU - Shu, Xiao Ou
AU - Smeets, Ann
AU - Southey, Melissa C.
AU - Stone, Jennifer
AU - Tamimi, Rulla M.
AU - Taylor, Jack A.
AU - Teras, Lauren R.
AU - Tomczyk, Katarzyna
AU - Troester, Melissa A.
AU - Truong, Thérèse
AU - Vachon, Celine M.
AU - Wang, Sophia S.
AU - Weinberg, Clarice R.
AU - Wildiers, Hans
AU - Willett, Walter
AU - Winham, Stacey J.
AU - Wolk, Alicja
AU - Yang, Xiaohong R.
AU - Zamora, M. Pilar
AU - Zheng, Wei
AU - Ziogas, Argyrios
AU - Dunning, Alison M.
AU - Pharoah, Paul D.P.
AU - García-Closas, Montserrat
AU - Schmidt, Marjanka K.
AU - Kraft, Peter
AU - Milne, Roger L.
AU - Lindström, Sara
AU - Easton, Douglas F.
AU - Chang-Claude, Jenny
N1 - Publisher Copyright:
© 2023. BioMed Central Ltd., part of Springer Nature.
PY - 2023/8/9
Y1 - 2023/8/9
N2 - 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.
AB - 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.
KW - Breast cancer
KW - European ancestry
KW - Gene-environment interactions
KW - Genetic epidemiology
UR - http://www.scopus.com/inward/record.url?scp=85167531154&partnerID=8YFLogxK
U2 - 10.1186/s13058-023-01691-8
DO - 10.1186/s13058-023-01691-8
M3 - Article
C2 - 37559094
AN - SCOPUS:85167531154
SN - 1465-542X
VL - 25
SP - 93
JO - Breast cancer research : BCR
JF - Breast cancer research : BCR
IS - 1
M1 - 93
ER -