A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Pooja Middha; Xiaoliang Wang; Sabine Behrens; Manjeet K Bolla; Qin Wang; Joe Dennis; Kyriaki Michailidou; Thomas U Ahearn; Irene L Andrulis; Hoda Anton-Culver; Volker Arndt; Kristan J Aronson; Paul L Auer; Annelie Augustinsson; Thaïs Baert; Laura E Beane Freeman; Heiko Becher; Matthias W Beckmann; Javier Benitez; Stig E Bojesen; Hiltrud Brauch; Hermann Brenner; Angela Brooks-Wilson; Daniele Campa; Federico Canzian; Angel Carracedo; Jose E Castelao; Stephen J Chanock; Georgia Chenevix-Trench; Emilie Cordina-Duverger; Fergus J Couch; Angela Cox; Simon S Cross; Kamila Czene; Laure Dossus; Pierre-Antoine Dugué; A Heather Eliassen; Mikael Eriksson; D Gareth Evans; Peter A Fasching; Jonine D Figueroa; Olivia Fletcher; Henrik Flyger; Marike Gabrielson; Manuela Gago-Dominguez; Graham G Giles; Anna González-Neira; Felix Grassmann; Sune F Nielsen; Børge G Nordestgaard; CTS Consortium

doi:10.1186/s13058-023-01691-8

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Pooja Middha, Xiaoliang Wang, Sabine Behrens, Manjeet K Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J Aronson, Paul L Auer, Annelie Augustinsson, Thaïs Baert, Laura E Beane Freeman, Heiko Becher, Matthias W Beckmann, Javier Benitez, Stig E BojesenHiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Daniele Campa, Federico Canzian, Angel Carracedo, Jose E Castelao, Stephen J Chanock, Georgia Chenevix-Trench, Emilie Cordina-Duverger, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Laure Dossus, Pierre-Antoine Dugué, A Heather Eliassen, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Jonine D Figueroa, Olivia Fletcher, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Graham G Giles, Anna González-Neira, Felix Grassmann, Sune F Nielsen, Børge G Nordestgaard, CTS Consortium

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Abstract

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.

Originalsprog	Engelsk
Artikelnummer	93
Tidsskrift	Breast Cancer Research
Vol/bind	25
Udgave nummer	1
Sider (fra-til)	93
ISSN	1465-542X
DOI	https://doi.org/10.1186/s13058-023-01691-8
Status	Udgivet - 9 aug. 2023

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10.1186/s13058-023-01691-8Licens: CC BY

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Middha, P., Wang, X., Behrens, S., Bolla, M. K., Wang, Q., Dennis, J., Michailidou, K., Ahearn, T. U., Andrulis, I. L., Anton-Culver, H., Arndt, V., Aronson, K. J., Auer, P. L., Augustinsson, A., Baert, T., Freeman, L. E. B., Becher, H., Beckmann, M. W., Benitez, J., ... CTS Consortium (2023). A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry. Breast Cancer Research, 25(1), 93. Artikel 93. https://doi.org/10.1186/s13058-023-01691-8

Middha, P, Wang, X, Behrens, S, Bolla, MK, Wang, Q, Dennis, J, Michailidou, K, Ahearn, TU, Andrulis, IL, Anton-Culver, H, Arndt, V, Aronson, KJ, Auer, PL, Augustinsson, A, Baert, T, Freeman, LEB, Becher, H, Beckmann, MW, Benitez, J, Bojesen, SE, Brauch, H, Brenner, H, Brooks-Wilson, A, Campa, D, Canzian, F, Carracedo, A, Castelao, JE, Chanock, SJ, Chenevix-Trench, G, Cordina-Duverger, E, Couch, FJ, Cox, A, Cross, SS, Czene, K, Dossus, L, Dugué, P-A, Eliassen, AH, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, JD, Fletcher, O, Flyger, H, Gabrielson, M, Gago-Dominguez, M, Giles, GG, González-Neira, A, Grassmann, F, Nielsen, SF , Nordestgaard, BG & CTS Consortium 2023, 'A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry', Breast Cancer Research, bind 25, nr. 1, 93, s. 93. https://doi.org/10.1186/s13058-023-01691-8

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title = "A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry",

abstract = "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.",

keywords = "Adult, Female, Humans, Gene-Environment Interaction, Genetic Predisposition to Disease, Breast Neoplasms/etiology, Bayes Theorem, Genome-Wide Association Study, Risk Factors, Polymorphism, Single Nucleotide, Case-Control Studies",

author = "Pooja Middha and Xiaoliang Wang and Sabine Behrens and Bolla, {Manjeet K} and Qin Wang and Joe Dennis and Kyriaki Michailidou and Ahearn, {Thomas U} and Andrulis, {Irene L} and Hoda Anton-Culver and Volker Arndt and Aronson, {Kristan J} and Auer, {Paul L} and Annelie Augustinsson and Tha{\"i}s Baert and Freeman, {Laura E Beane} and Heiko Becher and Beckmann, {Matthias W} and Javier Benitez and Bojesen, {Stig E} and Hiltrud Brauch and Hermann Brenner and Angela Brooks-Wilson and Daniele Campa and Federico Canzian and Angel Carracedo and Castelao, {Jose E} and Chanock, {Stephen J} and Georgia Chenevix-Trench and Emilie Cordina-Duverger and Couch, {Fergus J} and Angela Cox and Cross, {Simon S} and Kamila Czene and Laure Dossus and Pierre-Antoine Dugu{\'e} and Eliassen, {A Heather} and Mikael Eriksson and Evans, {D Gareth} and Fasching, {Peter A} and Figueroa, {Jonine D} and Olivia Fletcher and Henrik Flyger and Marike Gabrielson and Manuela Gago-Dominguez and Giles, {Graham G} and Anna Gonz{\'a}lez-Neira and Felix Grassmann and Nielsen, {Sune F} and Nordestgaard, {B{\o}rge G} and {CTS Consortium}",

note = "{\textcopyright} 2023. BioMed Central Ltd., part of Springer Nature.",

year = "2023",

month = aug,

day = "9",

doi = "10.1186/s13058-023-01691-8",

language = "English",

volume = "25",

pages = "93",

journal = "Breast Cancer Research",

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TY - JOUR

T1 - A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

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 - Nielsen, Sune F

AU - Nordestgaard, Børge G

AU - CTS Consortium

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 - 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

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U2 - 10.1186/s13058-023-01691-8

DO - 10.1186/s13058-023-01691-8

M3 - Journal article

C2 - 37559094

SN - 1465-542X

VL - 25

SP - 93

JO - Breast Cancer Research

JF - Breast Cancer Research

IS - 1

M1 - 93

ER -

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

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