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
Authors: Milne Roger L. , Herranz Jesús , Michailidou Kyriaki , Dennis Joe , Tyrer Jonathan P. , Zamora M. Pilar , Arias-Perez José Ignacio , González-Neira Anna , Pita Guillermo , Alonso M. Rosario , Wang Qin , Bolla Manjeet K. , Czene Kamila , Eriksson Mikael , Humphreys Keith , Darabi Hatef , Li Jingmei , Anton-Culver Hoda , Neuhausen Susan L. , Ziogas Argyrios , Clarke Christina A. , Hopper John L. , Dite Gillian S. , Apicella Carmel , Southey Melissa C. , Chenevix-Trench Georgia ,   kConFab Investigators,   Australian Ovarian Cancer Study Group, Swerdlow Anthony , Ashworth Alan , Orr Nicholas , Schoemaker Minouk , Jakubowska Anna , Lubinski Jan , Jaworska-Bieniek Katarzyna , Durda Katarzyna , Andrulis Irene L. , Knight Julia A. , Glendon Gord , Mulligan Anna Marie , Bojesen Stig E. , Nordestgaard Børge G. , Flyger Henrik , Nevanlinna Heli , Muranen Taru A. , Aittomäki Kristiina , Blomqvist Carl , Chang-Claude Jenny , Rudolph Anja , Seibold Petra , Flesch-Janys Dieter , Wang Xianshu , Olson Janet E. , Vachon Celine , Purrington Kristen , Winqvist Robert , Pylkäs Katri , Jukkola-Vuorinen Arja , Grip Mervi , Dunning Alison M. , Shah Mitul , Guénel Pascal , Truong Thérèse , Sanchez Marie , Mulot Claire , Brenner Hermann , Dieffenbach Aida Karina , Arndt Volker , Stegmaier Christa , Lindblom Annika , Margolin Sara , Hooning Maartje J. , Hollestelle Antoinette , Collée J. Margriet , Jager Agnes , Cox Angela , Brock Ian W. , Reed Malcolm W.R. , Devilee Peter , Tollenaar Robert A.E.M. , Seynaeve Caroline , Haiman Christopher A. , Henderson Brian E. , Schumacher Fredrick , Le Marchand Loic , Simard Jacques , Dumont Martine , Soucy Penny , Dörk Thilo , Bogdanova Natalia V. , Hamann Ute , Försti Asta , Rüdiger Thomas , Ulmer Hans-Ulrich , Fasching Peter A. , Häberle Lothar , Ekici Arif B. , Beckmann Matthias W. , Fletcher Olivia , Johnson Nichola , dos Santos Silva Isabel , Peto Julian , Radice Paolo , Peterlongo Paolo , Peissel Bernard , Mariani Paolo , Giles Graham G. , Severi Gianluca , Baglietto Laura , Sawyer Elinor , Tomlinson Ian , Kerin Michael , Miller Nicola , Marme Federik , Burwinkel Barbara , Mannermaa Arto , Kataja Vesa , Kosma Veli-Matti , Hartikainen Jaana M. , Lambrechts Diether , Yesilyurt Betul T. , Floris Giuseppe , Leunen Karin , Alnæs Grethe Grenaker , Kristensen Vessela , Børresen-Dale Anne-Lise , García-Closas Montserrat , Chanock Stephen J. , Lissowska Jolanta , Figueroa Jonine D. , Schmidt Marjanka K. , Broeks Annegien , Verhoef Senno , Rutgers Emiel J. , Brauch Hiltrud , Brüning Thomas , Ko Yon-Dschun ,   The GENICA Network, Couch Fergus J. , Toland Amanda E. ,   The TNBCC, Yannoukakos Drakoulis , Pharoah Paul D.P. , Hall Per , Benítez Javier , Malats Núria , Easton Douglas F. 
Published: November 2013

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 &lt; 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 &lt; 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 &lt; 10−8. Results from the second analytic approach were consistent with those from the first (P &gt; 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.