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. 2014 Apr 1;23(7):1934-46.
doi: 10.1093/hmg/ddt581. Epub 2013 Nov 15.

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

Roger L Milne  1 , Jesús Herranz, Kyriaki Michailidou, Joe Dennis, Jonathan P Tyrer, M Pilar Zamora, José Ignacio Arias-Perez, Anna González-Neira, Guillermo Pita, M Rosario Alonso, Qin Wang, Manjeet K Bolla, Kamila Czene, Mikael Eriksson, Keith Humphreys, Hatef Darabi, Jingmei Li, Hoda Anton-Culver, Susan L Neuhausen, Argyrios Ziogas, Christina A Clarke, John L Hopper, Gillian S Dite, Carmel Apicella, Melissa C Southey, Georgia Chenevix-Trench; kConFab Investigators; Australian Ovarian Cancer Study Group; Anthony Swerdlow, Alan Ashworth, Nicholas Orr, Minouk Schoemaker, Anna Jakubowska, Jan Lubinski, Katarzyna Jaworska-Bieniek, Katarzyna Durda, Irene L Andrulis, Julia A Knight, Gord Glendon, Anna Marie Mulligan, Stig E Bojesen, Børge G Nordestgaard, Henrik Flyger, Heli Nevanlinna, Taru A Muranen, Kristiina Aittomäki, Carl Blomqvist, Jenny Chang-Claude, Anja Rudolph, Petra Seibold, Dieter Flesch-Janys, Xianshu Wang, Janet E Olson, Celine Vachon, Kristen Purrington, Robert Winqvist, Katri Pylkäs, Arja Jukkola-Vuorinen, Mervi Grip, Alison M Dunning, Mitul Shah, Pascal Guénel, Thérèse Truong, Marie Sanchez, Claire Mulot, Hermann Brenner, Aida Karina Dieffenbach, Volker Arndt, Christa Stegmaier, Annika Lindblom, Sara Margolin, Maartje J Hooning, Antoinette Hollestelle, J Margriet Collée, Agnes Jager, Angela Cox, Ian W Brock, Malcolm W R Reed, Peter Devilee, Robert A E M Tollenaar, Caroline Seynaeve, Christopher A Haiman, Brian E Henderson, Fredrick Schumacher, Loic Le Marchand, Jacques Simard, Martine Dumont, Penny Soucy, Thilo Dörk, Natalia V Bogdanova, Ute Hamann, Asta Försti, Thomas Rüdiger, Hans-Ulrich Ulmer, Peter A Fasching, Lothar Häberle, Arif B Ekici, Matthias W Beckmann, Olivia Fletcher, Nichola Johnson, Isabel dos Santos Silva, Julian Peto, Paolo Radice, Paolo Peterlongo, Bernard Peissel, Paolo Mariani, Graham G Giles, Gianluca Severi, Laura Baglietto, Elinor Sawyer, Ian Tomlinson, Michael Kerin, Nicola Miller, Federik Marme, Barbara Burwinkel, Arto Mannermaa, Vesa Kataja, Veli-Matti Kosma, Jaana M Hartikainen, Diether Lambrechts, Betul T Yesilyurt, Giuseppe Floris, Karin Leunen, Grethe Grenaker Alnæs, Vessela Kristensen, Anne-Lise Børresen-Dale, Montserrat García-Closas, Stephen J Chanock, Jolanta Lissowska, Jonine D Figueroa, Marjanka K Schmidt, Annegien Broeks, Senno Verhoef, Emiel J Rutgers, Hiltrud Brauch, Thomas Brüning, Yon-Dschun Ko; GENICA Network; Fergus J Couch, Amanda E Toland; TNBCC; Drakoulis Yannoukakos, Paul D P Pharoah, Per Hall, Javier Benítez, Núria Malats, Douglas F Easton
Collaborators, Affiliations

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

Roger L Milne et al. Hum Mol Genet. .

Abstract

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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Figures

Figure 1.
Figure 1.
Q–Q plots from the first set of analyses based on the χ2 statistics from the 1 d.f. LRT for (A) overall breast cancer, (B) oestrogen receptor (ER)-positive breast cancer and (C) ER-negative breast cancer.
Figure 2.
Figure 2.
Schematic representation of the two strategies applies to assess pairwise interactions in susceptibility to overall breast cancer risk between the 70 917 SNPs considered.
See this image and copyright information in PMC

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