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 LE, Becher H, Beckmann M, 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 PA, Eliassen AH, Eriksson M, Evans DG, Fasching P, Figueroa JD, Fletcher O, Flyger H, Gabrielson M, Gago-Dominguez M, Giles GG, González-Neira A, Grassmann F, Grundy A, Guénel P, Haiman CA, Håkansson N, Hall P, Hamann U, Hankinson SE, Harkness EF, Holleczek B, Hoppe R, Hopper JL, Houlston RS, Howell A, Hunter DJ, Ingvar C, Isaksson K, Jernström H, John EM, Jones ME, Kaaks R, Keeman R, Kitahara CM, Ko YD, Koutros S, Kurian AW, Lacey JV, Lambrechts D, Larson NL, Larsson S, Le Marchand L, Lejbkowicz F, Li S, Linet M, Lissowska J, Martinez ME, Maurer T, Mulligan AM, Mulot C, Murphy RA, Newman WG, Nielsen SF, Nordestgaard BG, Norman A, O'Brien KM, Olson JE, Patel AV, Prentice R, Rees-Punia E, Rennert G, Rhenius V, Ruddy KJ, Sandler DP, Scott CG, Shah M, Shu XO, Smeets A, Southey MC, Stone J, Tamimi RM, Taylor JA, Teras LR, Tomczyk K, Troester MA, Truong T, Vachon CM, Wang SS, Weinberg CR, Wildiers H, Willett W, Winham SJ, Wolk A, Yang XR, Zamora MP, Zheng W, Ziogas A, Dunning AM, Pharoah PD, García-Closas M, Schmidt MK, Kraft P, Milne RL, Lindström S, Easton DF, Chang-Claude J (2023)
Publication Type: Journal article
Publication year: 2023
Book Volume: 25
Pages Range: 93-
Journal Issue: 1
DOI: 10.1186/s13058-023-01691-8
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.
APA:
Middha, P., Wang, X., Behrens, S., Bolla, M.K., Wang, Q., Dennis, J.,... Chang-Claude, J. (2023). A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry. Breast Cancer Research, 25(1), 93-. https://doi.org/10.1186/s13058-023-01691-8
MLA:
Middha, Pooja, et al. "A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry." Breast Cancer Research 25.1 (2023): 93-.
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