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, 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 ZiogasChristina A Clarke, John L Hopper, Gillian S Dite, Carmel Apicella, Melissa C Southey, Georgia Chenevix-Trench, 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, kConFab Investigators

27 Citationer (Scopus)

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 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.
OriginalsprogEngelsk
TidsskriftHuman Molecular Genetics
Vol/bind23
Udgave nummer7
Sider (fra-til)1934-1946
Antal sider12
ISSN0964-6906
DOI
StatusUdgivet - 1 apr. 2014

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