Article open access publication

Gene–environment interactions involving functional variants: Results from the Breast Cancer Association Consortium

International Journal of Cancer, Wiley, ISSN 0020-7136

Volume 141, 9, 2017

DOI:10.1002/ijc.30859, Dimensions: pub.1090344119, PMC: PMC5601244, PMID: 28670784,



  1. (1) German Cancer Research Center, grid.7497.d
  2. (2) University of Melbourne, grid.1008.9
  3. (3) Netherlands Cancer Institute–Antoni van Leeuwenhoek Hospital Division of Molecular Pathology Amsterdam The Netherlands
  4. (4) University of California, Los Angeles, grid.19006.3e
  5. (5) University Hospital Erlangen, Friedrich‐Alexander University Erlangen‐Nuremberg, Comprehensive Cancer Center Erlangen‐EMN Department of Gynaecology and Obstetrics Erlangen Germany
  6. (6) Complejo Hospitalario Universitario de Santiago, grid.411048.8
  7. (7) University of California, San Diego, grid.266100.3
  8. (8) Instituto de Investigación Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo‐SERGAS Oncology and Genetics Unit Vigo Spain
  9. (9) CESP–Cancer and Environment team, INSERM U1018, Université Paris‐Sud, Université Paris‐Saclay Villejuif France
  10. (10) Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital Herlev Denmark
  11. (11) Herlev and Gentofte Hospital, Copenhagen University Hospital Department of Clinical Biochemistry Herlev Denmark
  12. (12) University of Copenhagen, grid.5254.6, KU
  13. (13) Epidemiology Research Program, American Cancer Society Atlanta GA
  14. (14) Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, grid.502798.1
  15. (15) University of Tübingen, grid.10392.39
  16. (16) Molecular Epidemiology Group, German Cancer Research Center (DKFZ) Heidelberg Germany
  17. (17) Imaging Center, Department of Clinical Pathology, Kuopio University Hospital Kuopio Finland
  18. (18) Institute of Clinical Medicine, University of Eastern Finland Pathology and Forensic Medicine Kuopio Finland
  19. (19) Translational Cancer Research Area, University of Eastern Finland Kuopio Finland
  20. (20) Department of Human Genetics, University of Leuven Laboratory for Translational Genetics Leuven Belgium
  21. (21) Vesalius Research Center, VIB Leuven Belgium
  22. (22) Leuven Multidisciplinary Breast Center, Department of Oncology, KU Leuven and Leuven Cancer Institute, University Hospitals Leuven Leuven Belgium
  23. (23) Institute for Medical Biometrics and Epidemiology, University Medical Center Hamburg‐Eppendorf Hamburg Germany
  24. (24) University Cancer Center Hamburg (UCCH), University Medical Center Hamburg‐Eppendorf Department of Cancer Epidemiology Hamburg Germany
  25. (25) Mayo Clinic Department of Laboratory Medicine and Pathology Rochester MN
  26. (26) Cancer Council Victoria, grid.3263.4
  27. (27) Genomics Center, Centre Hospitalier Universitaire de Québec Research Center, Laval University Québec City QC Canada
  28. (28) McGill University, grid.14709.3b
  29. (29) Royal Victoria Hospital, McGill University Division of Clinical Epidemiology Montréal QC Canada
  30. (30) University of Edinburgh, grid.4305.2
  31. (31) National Cancer Institute Division of Cancer Epidemiology and Genetics Bethesda MD
  32. (32) The Cyprus Institute of Neurology and Genetics, Nicosia Department of Electron Microscopy/Molecular Pathology Nicosia Cyprus
  33. (33) University of Cambridge, grid.5335.0
  34. (34) Karolinska Institute, grid.4714.6
  35. (35) University of Sheffield, grid.11835.3e
  36. (36) The Institute of Cancer Research Division of Genetics and Epidemiology Sutton, London United Kingdom
  37. (37) The Institute of Cancer Research Division of Breast Cancer Research Sutton, London United Kingdom
  38. (38) The Netherlands Cancer Institute–Antoni van Leeuwenhoek Hospital Division of Psychosocial Research and Epidemiology Amsterdam The Netherlands
  39. (39) Research Group Genetic Cancer Epidemiology, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg‐Eppendorf Hamburg Germany


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.


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