TY - JOUR
T1 - A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry
AU - CTS Consortium
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 - 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 - Harkness, Elaine F
AU - Howell, Anthony
N1 - © 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 (OR
int = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (OR
int = 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 (OR
int = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (OR
int = 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 - Adult
KW - Female
KW - Humans
KW - Gene-Environment Interaction
KW - Genetic Predisposition to Disease
KW - Breast Neoplasms/etiology
KW - Bayes Theorem
KW - Genome-Wide Association Study
KW - Risk Factors
KW - Polymorphism, Single Nucleotide
KW - Case-Control Studies
UR - http://www.scopus.com/inward/record.url?scp=85167531154&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/8e9a7c10-f1ec-3e9c-b397-e7403594edae/
U2 - 10.1186/s13058-023-01691-8
DO - 10.1186/s13058-023-01691-8
M3 - Article
C2 - 37559094
SN - 1465-5411
VL - 25
JO - Breast cancer research : BCR
JF - Breast cancer research : BCR
IS - 1
M1 - 93
ER -