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Hum Mol Genet. 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.

Milne RL1, Herranz J, Michailidou K, Dennis J, Tyrer JP, Zamora MP, Arias-Perez JI, González-Neira A, Pita G, Alonso MR, Wang Q, Bolla MK, Czene K, Eriksson M, Humphreys K, Darabi H, Li J, Anton-Culver H, Neuhausen SL, Ziogas A, Clarke CA, Hopper JL, Dite GS, Apicella C, Southey MC, Chenevix-Trench G; kConFab Investigators; Australian Ovarian Cancer Study Group, Swerdlow A, Ashworth A, Orr N, Schoemaker M, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Andrulis IL, Knight JA, Glendon G, Mulligan AM, Bojesen SE, Nordestgaard BG, Flyger H, Nevanlinna H, Muranen TA, Aittomäki K, Blomqvist C, Chang-Claude J, Rudolph A, Seibold P, Flesch-Janys D, Wang X, Olson JE, Vachon C, Purrington K, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Dunning AM, Shah M, Guénel P, Truong T, Sanchez M, Mulot C, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Lindblom A, Margolin S, Hooning MJ, Hollestelle A, Collée JM, Jager A, Cox A, Brock IW, Reed MW, Devilee P, Tollenaar RA, Seynaeve C, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Simard J, Dumont M, Soucy P, Dörk T, Bogdanova NV, Hamann U, Försti A, Rüdiger T, Ulmer HU, Fasching PA, Häberle L, Ekici AB, Beckmann MW, Fletcher O, Johnson N, dos Santos Silva I, Peto J, Radice P, Peterlongo P, Peissel B, Mariani P, Giles GG, Severi G, Baglietto L, Sawyer E, Tomlinson I, Kerin M, Miller N, Marme F, Burwinkel B, Mannermaa A, Kataja V, Kosma VM, Hartikainen JM, Lambrechts D, Yesilyurt BT, Floris G, Leunen K, Alnæs GG, Kristensen V, Børresen-Dale AL, García-Closas M, Chanock SJ, Lissowska J, Figueroa JD, Schmidt MK, Broeks A, Verhoef S, Rutgers EJ, Brauch H, Brüning T, Ko YD; GENICA Network, Couch FJ, Toland AE; TNBCC, Yannoukakos D, Pharoah PD, Hall P, Benítez J, Malats N, Easton DF.

Author information

1
Human Cancer Genetics Programme and.

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.

PMID:
24242184
PMCID:
PMC3943524
DOI:
10.1093/hmg/ddt581
[Indexed for MEDLINE]
Free PMC Article

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