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. 2010;12(6):R110.
doi: 10.1186/bcr2797. Epub 2010 Dec 31.

Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: a combined case-control study

Roger L Milne  1 , Mia M Gaudet, Amanda B Spurdle, Peter A Fasching, Fergus J Couch, Javier Benítez, José Ignacio Arias Pérez, M Pilar Zamora, Núria Malats, Isabel Dos Santos Silva, Lorna J Gibson, Olivia Fletcher, Nichola Johnson, Hoda Anton-Culver, Argyrios Ziogas, Jonine Figueroa, Louise Brinton, Mark E Sherman, Jolanta Lissowska, John L Hopper, Gillian S Dite, Carmel Apicella, Melissa C Southey, Alice J Sigurdson, Martha S Linet, Sara J Schonfeld, D Michal Freedman, Arto Mannermaa, Veli-Matti Kosma, Vesa Kataja, Päivi Auvinen, Irene L Andrulis, Gord Glendon, Julia A Knight, Nayana Weerasooriya, Angela Cox, Malcolm Wr Reed, Simon S Cross, Alison M Dunning, Shahana Ahmed, Mitul Shah, Hiltrud Brauch, Yon-Dschun Ko, Thomas Brüning; GENICA Network; Diether Lambrechts, Joke Reumers, Ann Smeets, Shan Wang-Gohrke, Per Hall, Kamila Czene, Jianjun Liu, Astrid K Irwanto, Georgia Chenevix-Trench, Helene Holland; kConFab; AOCS; Graham G Giles, Laura Baglietto, Gianluca Severi, Stig E Bojensen, Børge G Nordestgaard, Henrik Flyger, Esther M John, Dee W West, Alice S Whittemore, Celine Vachon, Janet E Olson, Zachary Fredericksen, Matthew Kosel, Rebecca Hein, Alina Vrieling, Dieter Flesch-Janys, Judith Heinz, Matthias W Beckmann, Katharina Heusinger, Arif B Ekici, Lothar Haeberle, Manjeet K Humphreys, Jonathan Morrison, Doug F Easton, Paul D Pharoah, Montserrat García-Closas, Ellen L Goode, Jenny Chang-Claude
Affiliations

Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: a combined case-control study

Roger L Milne et al. Breast Cancer Res. 2010.

Abstract

Introduction: Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium.

Methods: We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects.

Results: These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar.

Conclusions: The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.

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Figures

Figure 1
Figure 1
Per-allele OR estimates for 11p15-rs3817198 (LSP1) stratified by number of live births (parous women only). For breast cancer disease subtypes defined by estrogen receptor (ER) and progesterone receptor (PR) status. The size of the box is inversely proportional to the standard error of the log OR estimate.
See this image and copyright information in PMC

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