Gene-environment interactions involving functional variants: Results from the Breast Cancer Association Consortium
- Barrdahl, M.
- Rudolph, A.
- Hopper, J.L.
- Southey, M.C.
- Broeks, A.
- Fasching, P.A.
- Beckmann, M.W.
- Gago-Dominguez, M.
- Castelao, J.E.
- Guénel, P.
- Truong, T.
- Bojesen, S.E.
- Gapstur, S.M.
- Gaudet, M.M.
- Brenner, H.
- Arndt, V.
- Brauch, H.
- Hamann, U.
- Mannermaa, A.
- Lambrechts, D.
- Jongen, L.
- Flesch-Janys, D.
- Thoene, K.
- Couch, F.J.
- Giles, G.G.
- Simard, J.
- Goldberg, M.S.
- Figueroa, J.
- Michailidou, K.
- Bolla, M.K.
- Dennis, J.
- Wang, Q.
- Eilber, U.
- Behrens, S.
- Czene, K.
- Hall, P.
- Cox, A.
- Cross, S.
- Swerdlow, A.
- Schoemaker, M.J.
- Dunning, A.M.
- Kaaks, R.
- Pharoah, P.D.P.
- Schmidt, M.
- Garcia-Closas, M.
- Easton, D.F.
- Milne, R.L.
- Chang-Claude, J.
DOIAbstract
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 SNPs 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, 31,605 controls) from the Breast Cancer Association Consortium (BCAC), in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor positive (ER+) and estrogen receptor negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four po...
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