Showing papers by "Nichola Johnson published in 2010"
Albert Einstein College of Medicine1, QIMR Berghofer Medical Research Institute2, University of California, Los Angeles3, Mayo Clinic4, Hospital Universitario La Paz5, University of London6, Institute of Cancer Research7, University of California, Irvine8, University of Melbourne9, University of Eastern Finland10, University of Toronto11, Mount Sinai Hospital12, Cancer Care Ontario13, University of Sheffield14, University of Cambridge15, Bosch16, Ruhr University Bochum17, Katholieke Universiteit Leuven18, University of Ulm19, Karolinska Institutet20, Genome Institute of Singapore21, Peter MacCallum Cancer Centre22, Monash University23, Cancer Council Victoria24, Copenhagen University Hospital25, Cancer Prevention Institute of California26, Stanford University27, German Cancer Research Center28, Eppendorf (Germany)29, University of Duisburg-Essen30, University of Erlangen-Nuremberg31
TL;DR: 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.
Abstract: 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. 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. 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. 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.
97 citations