TY - JOUR

T1 - Gene-environment interactions involving functional variants

T2 - Results from the Breast Cancer Association Consortium

AU - Barrdahl, Myrto

AU - Rudolph, Anja

AU - Hopper, John L

AU - Southey, Melissa C

AU - Broeks, Annegien

AU - Fasching, Peter A

AU - Beckmann, Matthias W

AU - Gago-Dominguez, Manuela

AU - Castelao, J Esteban

AU - Guénel, Pascal

AU - Truong, Thérèse

AU - Bojesen, Stig E

AU - Gapstur, Susan M

AU - Gaudet, Mia M

AU - Brenner, Hermann

AU - Arndt, Volker

AU - Brauch, Hiltrud

AU - Hamann, Ute

AU - Mannermaa, Arto

AU - Lambrechts, Diether

AU - Jongen, Lynn

AU - Flesch-Janys, Dieter

AU - Thoene, Kathrin

AU - Couch, Fergus J

AU - Giles, Graham G

AU - Simard, Jacques

AU - Goldberg, Mark S

AU - Figueroa, Jonine

AU - Michailidou, Kyriaki

AU - Bolla, Manjeet K

AU - Dennis, Joe

AU - Wang, Qin

AU - Eilber, Ursula

AU - Behrens, Sabine

AU - Czene, Kamila

AU - Hall, Per

AU - Cox, Angela

AU - Cross, Simon

AU - Swerdlow, Anthony

AU - Schoemaker, Minouk J

AU - Dunning, Alison M

AU - Kaaks, Rudolf

AU - Pharoah, Paul D P

AU - Schmidt, Marjanka

AU - Garcia-Closas, Montserrat

AU - Easton, Douglas F

AU - Milne, Roger L

AU - Chang-Claude, Jenny

N1 - © 2017 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.

PY - 2017/11/1

Y1 - 2017/11/1

N2 - Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene-environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (ORint  = 0.77, 95% CI: 0.67-0.88, pint  = 1.8 × 10(-4) ). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16-1.59, pint  = 1.9 × 10(-5) ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint  = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10(-4) ) and between 8q23-rs13267382 and age at first full-term pregnancy (ORint  = 0.89, 95% CI: 0.83-0.95, pint  = 5.2 × 10(-4) ). While these results do not suggest any strong gene-environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

AB - Investigating the most likely causal variants identified by fine-mapping analyses may improve the power to detect gene-environment interactions. We assessed the interplay between 70 single nucleotide polymorphisms identified by genetic fine-scale mapping of susceptibility loci and 11 epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP < 0.80) when assuming a true prior interaction probability of 0.01. The strongest interaction result in relation to overall breast cancer risk was found between CFLAR-rs7558475 and current smoking (ORint  = 0.77, 95% CI: 0.67-0.88, pint  = 1.8 × 10(-4) ). The interaction with the strongest statistical evidence was found between 5q14-rs7707921 and alcohol consumption (ORint =1.36, 95% CI: 1.16-1.59, pint  = 1.9 × 10(-5) ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint  = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10(-4) ) and between 8q23-rs13267382 and age at first full-term pregnancy (ORint  = 0.89, 95% CI: 0.83-0.95, pint  = 5.2 × 10(-4) ). While these results do not suggest any strong gene-environment interactions, our results may still be useful to inform experimental studies. These may in turn, shed light on the potential interactions observed.

KW - Alcohol Drinking

KW - Breast Neoplasms

KW - CASP8 and FADD-Like Apoptosis Regulating Protein

KW - Estrogen Receptor alpha

KW - Female

KW - Gene-Environment Interaction

KW - Genetic Association Studies

KW - Genetic Predisposition to Disease

KW - Humans

KW - Polymorphism, Single Nucleotide

KW - Risk Factors

KW - Smoking

KW - Journal Article

U2 - 10.1002/ijc.30859

DO - 10.1002/ijc.30859

M3 - Journal article

C2 - 28670784

VL - 141

SP - 1830

EP - 1840

JO - International Journal of Cancer

JF - International Journal of Cancer

SN - 0020-7136

IS - 9

ER -