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

TY - JOUR

T1 - 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

AU - Milne, Roger L

AU - Herranz, Jesús

AU - Michailidou, Kyriaki

AU - Dennis, Joe

AU - Tyrer, Jonathan P

AU - Zamora, M Pilar

AU - Arias-Perez, José Ignacio

AU - González-Neira, Anna

AU - Pita, Guillermo

AU - Alonso, M Rosario

AU - Wang, Qin

AU - Bolla, Manjeet K

AU - Czene, Kamila

AU - Eriksson, Mikael

AU - Humphreys, Keith

AU - Darabi, Hatef

AU - Li, Jingmei

AU - Anton-Culver, Hoda

AU - Neuhausen, Susan L

AU - Ziogas, Argyrios

AU - Clarke, Christina A

AU - Hopper, John L

AU - Dite, Gillian S

AU - Apicella, Carmel

AU - Southey, Melissa C

AU - Chenevix-Trench, Georgia

AU - Swerdlow, Anthony

AU - Ashworth, Alan

AU - Orr, Nicholas

AU - Schoemaker, Minouk

AU - Jakubowska, Anna

AU - Lubinski, Jan

AU - Jaworska-Bieniek, Katarzyna

AU - Durda, Katarzyna

AU - Andrulis, Irene L

AU - Knight, Julia A

AU - Glendon, Gord

AU - Mulligan, Anna Marie

AU - Bojesen, Stig E

AU - Nordestgaard, Børge G

AU - Flyger, Henrik

AU - Nevanlinna, Heli

AU - Muranen, Taru A

AU - Aittomäki, Kristiina

AU - Blomqvist, Carl

AU - Chang-Claude, Jenny

AU - Rudolph, Anja

AU - Seibold, Petra

AU - Flesch-Janys, Dieter

AU - Wang, Xianshu

AU - Olson, Janet E

AU - Vachon, Celine

AU - Purrington, Kristen

AU - Winqvist, Robert

AU - Pylkäs, Katri

AU - Jukkola-Vuorinen, Arja

AU - Grip, Mervi

AU - Dunning, Alison M

AU - Shah, Mitul

AU - Guénel, Pascal

AU - Truong, Thérèse

AU - Sanchez, Marie

AU - Mulot, Claire

AU - Brenner, Hermann

AU - Dieffenbach, Aida Karina

AU - Arndt, Volker

AU - Stegmaier, Christa

AU - Lindblom, Annika

AU - Margolin, Sara

AU - Hooning, Maartje J

AU - Hollestelle, Antoinette

AU - Collée, J Margriet

AU - Jager, Agnes

AU - Cox, Angela

AU - Brock, Ian W

AU - Reed, Malcolm W R

AU - Devilee, Peter

AU - Tollenaar, Robert A E M

AU - Seynaeve, Caroline

AU - Haiman, Christopher A

AU - Henderson, Brian E

AU - Schumacher, Fredrick

AU - Le Marchand, Loic

AU - Simard, Jacques

AU - Dumont, Martine

AU - Soucy, Penny

AU - Dörk, Thilo

AU - Bogdanova, Natalia V

AU - Hamann, Ute

AU - Försti, Asta

AU - Rüdiger, Thomas

AU - Ulmer, Hans-Ulrich

AU - Fasching, Peter A

AU - Häberle, Lothar

AU - Ekici, Arif B

AU - Beckmann, Matthias W

AU - Fletcher, Olivia

AU - Johnson, Nichola

AU - dos Santos Silva, Isabel

AU - Peto, Julian

AU - Radice, Paolo

AU - Peterlongo, Paolo

AU - Peissel, Bernard

AU - Mariani, Paolo

AU - Giles, Graham G

AU - Severi, Gianluca

AU - Baglietto, Laura

AU - Sawyer, Elinor

AU - Tomlinson, Ian

AU - Kerin, Michael

AU - Miller, Nicola

AU - Marme, Federik

AU - Burwinkel, Barbara

AU - Mannermaa, Arto

AU - Kataja, Vesa

AU - Kosma, Veli-Matti

AU - Hartikainen, Jaana M

AU - Lambrechts, Diether

AU - Yesilyurt, Betul T

AU - Floris, Giuseppe

AU - Leunen, Karin

AU - Alnæs, Grethe Grenaker

AU - Kristensen, Vessela

AU - Børresen-Dale, Anne-Lise

AU - García-Closas, Montserrat

AU - Chanock, Stephen J

AU - Lissowska, Jolanta

AU - Figueroa, Jonine D

AU - Schmidt, Marjanka K

AU - Broeks, Annegien

AU - Verhoef, Senno

AU - Rutgers, Emiel J

AU - Brauch, Hiltrud

AU - Brüning, Thomas

AU - Ko, Yon-Dschun

AU - Couch, Fergus J

AU - Toland, Amanda E

AU - Yannoukakos, Drakoulis

AU - Pharoah, Paul D P

AU - Hall, Per

AU - Benítez, Javier

AU - Malats, Núria

AU - Easton, Douglas F

AU - KConFab Investigators

AU - Harth, Volker

N1 - Dieter Flesch-Janys [ 43 ] Univ Clin Hamburg Eppendorf, Dept Canc Epidemiol, Clin Canc Registry, Hamburg, Germany [ 44 ] Univ Clin Hamburg Eppendorf, Inst Med Biometr & Epidemiol, Hamburg, Germany

PY - 2014/4/1

Y1 - 2014/4/1

N2 - 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.

AB - 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.

U2 - 10.1093/hmg/ddt581

DO - 10.1093/hmg/ddt581

M3 - SCORING: Journal article

C2 - 24242184

VL - 23

SP - 1934

EP - 1946

JO - HUM MOL GENET

JF - HUM MOL GENET

SN - 0964-6906

IS - 7

ER -