Article open access publication

A large-scale assessment of two-way SNP interactions in breast cancer susceptibility using 46 450 cases and 42 461 controls from the breast cancer association consortium

Human Molecular Genetics, Oxford University Press (OUP), ISSN 1460-2083

Volume 23, 7, 2014

DOI:10.1093/hmg/ddt581, Dimensions: pub.1032292269, PMC: PMC3943524, PMID: 24242184,

Authors

Milne, Roger L. (1) (2) (3)
Herranz, Jesús (3) (4)
Wang, Qin (5)
Swerdlow, Anthony (17) (18)
Ashworth, Alan (17) (18) (19)
Orr, Nicholas (17) (19)
Andrulis, Irene L. (22) (23)
Knight, Julia A. (23) (24)
Bojesen, Stig E. (28) (29)
Guénel, Pascal (41) (42)
Truong, Thérèse (41) (42)
Sanchez, Marie (41) (42)
Mulot, Claire (42) (43)
Brenner, Hermann (44) (45)
Devilee, Peter (52) (53)
Försti, Asta (60) (61)
Fasching, Peter A. (64) (65)
Mariani, Paolo (69) (71)
Giles, Graham G (1) (2)
Tomlinson, Ian (73) (74)
Marme, Federik (76) (77)
Burwinkel, Barbara (45) (77)
Mannermaa, Arto (78) (79) (80)
Kataja, Vesa (78) (79) (81)
Kosma, Veli-Matti (78) (79) (80)
Hartikainen, Jaana M (78) (79) (80)
Garcia-Closas, Montserrat (17) (18) (19) (86)
Brauch, Hiltrud (89) (90)
Hall, Per (10)
Benítez, Javier (3) (9) (95)

Affiliations

Organisations

  1. (1) Cancer Council Victoria, grid.3263.4
  2. (2) Centre for Epidemiology and Biostatistics, School of Population Health and
  3. (3) Human Cancer Genetics Programme and
  4. (4) Madrid Institute for Advanced Studies, grid.429045.e
  5. (5) Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care and
  6. (6) University of Cambridge, grid.5335.0
  7. (7) Hospital Universitario La Paz, grid.81821.32
  8. (8) Hospital Monte Naranco, grid.414858.4
  9. (9) Spanish National Cancer Research Centre, grid.7719.8
  10. (10) Department of Medical Epidemiology and Biostatistics
  11. (11) Genome Institute of Singapore, grid.418377.e
  12. (12) University of California, Irvine, grid.266093.8
  13. (13) City Of Hope National Medical Center, grid.410425.6
  14. (14) Cancer Prevention Institute of California, grid.280669.3
  15. (15) University of Melbourne, grid.1008.9
  16. (16) QIMR Berghofer Medical Research Institute, grid.1049.c
  17. (17) Division of Breast Cancer Research
  18. (18) Institute of Cancer Research, grid.18886.3f
  19. (19) Breakthrough Breast Cancer Research Centre and
  20. (20) Pomeranian Medical University, grid.107950.a
  21. (21) Medical University of Warsaw, grid.13339.3b
  22. (22) Department of Molecular Genetics
  23. (23) Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
  24. (24) Division of Epidemiology, Dalla Lana School of Public Health and
  25. (25) Lunenfeld-Tanenbaum Research Institute, grid.250674.2
  26. (26) University Health Network, grid.231844.8
  27. (27) University of Toronto, grid.17063.33
  28. (28) Copenhagen General Population Study
  29. (29) Department of Clinical Biochemistry and
  30. (30) University of Copenhagen, grid.5254.6, KU
  31. (31) Helsinki University Central Hospital, grid.15485.3d
  32. (32) Department of Clinical Genetics and
  33. (33) Division of Cancer Epidemiology
  34. (34) Department of Cancer Epidemiology/Clinical Cancer Registry and
  35. (35) University Medical Center Hamburg-Eppendorf, grid.13648.38
  36. (36) Department of Laboratory Medicine and Pathology and
  37. (37) Mayo Clinic, grid.66875.3a
  38. (38) Laboratory of Cancer Genetics and Tumor Biology, Department of Clinical Chemistry and Biocenter Oulu
  39. (39) Department of Oncology and
  40. (40) Department of Surgery, Oulu University Hospital, University of Oulu, Oulu, Finland
  41. (41) University of Paris-Sud, grid.5842.b
  42. (42) French Institute of Health and Medical Research, grid.7429.8
  43. (43) Centre de Ressources Biologiques EPIGENETEC, Paris, France
  44. (44) Division of Clinical Epidemiology and Aging Research
  45. (45) German Cancer Research Center, grid.7497.d
  46. (46) Krebsregister Saarland, grid.482902.5
  47. (47) Department of Molecular Medicine and Surgery and
  48. (48) Karolinska Institute, grid.4714.6
  49. (49) Department of Medical Oncology, Family Cancer Clinic and
  50. (50) Erasmus University Medical Center, grid.5645.2
  51. (51) University of Sheffield, grid.11835.3e
  52. (52) Department of Human Genetics
  53. (53) Department of Pathology and
  54. (54) Leiden University Medical Center, grid.10419.3d
  55. (55) University of Southern California, grid.42505.36
  56. (56) University of Hawaii at Manoa, grid.410445.0
  57. (57) Centre Hospitalier Universitaire de Québec, grid.411081.d
  58. (58) Department of Obstetrics and Gynaecology and
  59. (59) Hannover Medical School, grid.10423.34
  60. (60) Division of Molecular Genetic Epidemiology and
  61. (61) Lund University, grid.4514.4
  62. (62) Städtisches Klinikum Karlsruhe, grid.419594.4
  63. (63) Klinikum Mittelbaden, grid.506801.a
  64. (64) University of California, Los Angeles, grid.19006.3e
  65. (65) University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
  66. (66) Institute of Human Genetics, University Hospital Erlangen, Friedrich Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
  67. (67) London School of Hygiene & Tropical Medicine, grid.8991.9
  68. (68) Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Preventive and Predictive Medicine and
  69. (69) FIRC Institute of Molecular Oncology, grid.7678.e
  70. (70) Fondazione IRCCS Istituto Nazionale dei Tumori, grid.417893.0
  71. (71) Cogentech Cancer Genetic Test Laboratory, Milan, Italy
  72. (72) King's College London, grid.13097.3c
  73. (73) University of Oxford, grid.4991.5
  74. (74) Wellcome Trust Centre for Human Genetics and
  75. (75) National University of Ireland, Galway, grid.6142.1
  76. (76) National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany
  77. (77) Department of Obstetrics and Gynecology and
  78. (78) School of Medicine, Institute of Clinical Medicine, Pathology and Forensic Medicine and
  79. (79) University of Eastern Finland, grid.9668.1
  80. (80) Department of Clinical Pathology and
  81. (81) Kuopio University Hospital, grid.410705.7
  82. (82) Flanders Institute for Biotechnology, grid.11486.3a
  83. (83) Universitair Ziekenhuis Leuven, grid.410569.f
  84. (84) Oslo University Hospital, grid.55325.34
  85. (85) University of Oslo, grid.5510.1
  86. (86) National Cancer Institute, grid.48336.3a
  87. (87) Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, grid.418165.f
  88. (88) Antoni van Leeuwenhoek Hospital, grid.430814.a
  89. (89) Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, grid.502798.1
  90. (90) University of Tübingen, grid.10392.39
  91. (91) Ruhr University Bochum, grid.5570.7
  92. (92) Department of Internal Medicine, Evangelische Kliniken Bonn GmbH, Johanniter Krankenhaus, Bonn, Germany
  93. (93) The Ohio State University, grid.261331.4
  94. (94) National Centre of Scientific Research Demokritos, grid.6083.d
  95. (95) Centre for Biomedical Network Research on Rare Diseases, grid.452372.5

Description

Part of the substantial unexplained familial aggregation of breast cancer may be due to interactions between common variants, but few studies have had adequate statistical power to detect interactions of realistic magnitude. We aimed to assess all two-way interactions in breast cancer susceptibility between 70,917 single nucleotide polymorphisms (SNPs) selected primarily based on prior evidence of a marginal effect. Thirty-eight international studies contributed data for 46,450 breast cancer cases and 42,461 controls of European origin as part of a multi-consortium project (COGS). First, SNPs were preselected based on evidence (P < 0.01) of a per-allele main effect, and all two-way combinations of those were evaluated by a per-allele (1 d.f.) test for interaction using logistic regression. Second, all 2.5 billion possible two-SNP combinations were evaluated using Boolean operation-based screening and testing, and SNP pairs with the strongest evidence of interaction (P < 10(-4)) were selected for more careful assessment by logistic regression. Under the first approach, 3277 SNPs were preselected, but an evaluation of all possible two-SNP combinations (1 d.f.) identified no interactions at P < 10(-8). Results from the second analytic approach were consistent with those from the first (P > 10(-10)). In summary, we observed little evidence of two-way SNP interactions in breast cancer susceptibility, despite the large number of SNPs with potential marginal effects considered and the very large sample size. This finding may have important implications for risk prediction, simplifying the modelling required. Further comprehensive, large-scale genome-wide interaction studies may identify novel interacting loci if the inherent logistic and computational challenges can be overcome.

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Times Cited: 27

Field Citation Ratio (FCR): 5.59

Relative Citation ratio (RCR): 0.83

Open Access Info

Green, Published