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 Ziogas; Christina 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

doi:10.1093/hmg/ddt581

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

Department of Clinical Medicine

24 Citations (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 < 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.

Original language	English
Journal	Human Molecular Genetics
Volume	23
Issue number	7
Pages (from-to)	1934-1946
Number of pages	13
ISSN	0964-6906
DOIs	https://doi.org/10.1093/hmg/ddt581
Publication status	Published - 1 Apr 2014

Keywords

Breast Neoplasms
Case-Control Studies
Epistasis, Genetic
Female
Genetic Predisposition to Disease
Genome-Wide Association Study
Humans
Logistic Models
Polymorphism, Single Nucleotide

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1093/hmg/ddt581

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Milne, R. L., Herranz, J., Michailidou, K., Dennis, J., Tyrer, J. P., Zamora, M. P., Arias-Perez, J. I., González-Neira, A., Pita, G., Alonso, M. R., Wang, Q., Bolla, M. K., Czene, K., Eriksson, M., Humphreys, K., Darabi, H., Li, J., Anton-Culver, H., Neuhausen, S. L., ... kConFab Investigators (2014). 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. Human Molecular Genetics, 23(7), 1934-1946. https://doi.org/10.1093/hmg/ddt581

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, Roger L; Herranz, Jesús; Michailidou, Kyriaki et al.

In: Human Molecular Genetics, Vol. 23, No. 7, 01.04.2014, p. 1934-1946.

Research output: Contribution to journal › Journal article › Research › peer-review

Milne, RL, 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, 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 & kConFab Investigators 2014, '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', Human Molecular Genetics, vol. 23, no. 7, pp. 1934-1946. https://doi.org/10.1093/hmg/ddt581

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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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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 - kConFab Investigators

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.

KW - Breast Neoplasms

KW - Case-Control Studies

KW - Epistasis, Genetic

KW - Female

KW - Genetic Predisposition to Disease

KW - Genome-Wide Association Study

KW - Humans

KW - Logistic Models

KW - Polymorphism, Single Nucleotide

U2 - 10.1093/hmg/ddt581

DO - 10.1093/hmg/ddt581

M3 - Journal article

C2 - 24242184

SN - 0964-6906

VL - 23

SP - 1934

EP - 1946

JO - Human Molecular Genetics

JF - Human Molecular Genetics

IS - 7

ER -

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

Abstract

Keywords

UN SDGs

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