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Gene–environment interactions involving functional variants: Results from the Breast Cancer Association Consortium
Author(s) -
Barrdahl Myrto,
Rudolph Anja,
Hopper John L.,
Southey Melissa C.,
Broeks Annegien,
Fasching Peter A.,
Beckmann Matthias W.,
GagoDominguez Manuela,
Castelao J. Esteban,
Guénel Pascal,
Truong Thérèse,
Bojesen Stig E.,
Gapstur Susan M.,
Gaudet Mia M.,
Brenner Hermann,
Arndt Volker,
Brauch Hiltrud,
Hamann Ute,
Mannermaa Arto,
Lambrechts Diether,
Jongen Lynn,
FleschJanys Dieter,
Thoene Kathrin,
Couch Fergus J.,
Giles Graham G.,
Simard Jacques,
Goldberg Mark S.,
Figueroa Jonine,
Michailidou Kyriaki,
Bolla Manjeet K.,
Dennis Joe,
Wang Qin,
Eilber Ursula,
Behrens Sabine,
Czene Kamila,
Hall Per,
Cox Angela,
Cross Simon,
Swerdlow Anthony,
Schoemaker Minouk J.,
Dunning Alison M.,
Kaaks Rudolf,
Pharoah Paul D.P.,
Schmidt Marjanka,
GarciaClosas Montserrat,
Easton Douglas F.,
Milne Roger L.,
ChangClaude Jenny
Publication year - 2017
Publication title -
international journal of cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.475
H-Index - 234
eISSN - 1097-0215
pISSN - 0020-7136
DOI - 10.1002/ijc.30859
Subject(s) - breast cancer , single nucleotide polymorphism , genome wide association study , cancer , oncology , estrogen receptor , disease , genetic association , medicine , genetics , biology , genotype , gene
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 (OR int = 0.77, 95% CI: 0.67–0.88, p int = 1.8 × 10 −4 ). The interaction with the strongest statistical evidence was found between 5q14‐rs7707921 and alcohol consumption (OR int =1.36, 95% CI: 1.16–1.59, p int = 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 (OR int = 1.26, 95% CI: 1.12–1.43, p int =1.8 × 10 −4 ) and between 8q23‐rs13267382 and age at first full‐term pregnancy (OR int = 0.89, 95% CI: 0.83–0.95, p int = 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.