TY  - JOUR
AU  - Rudolph, Anja
AU  - Song, Minsun
AU  - Brook, Mark N
AU  - Milne, Roger L
AU  - Mavaddat, Nasim
AU  - Michailidou, Kyriaki
AU  - Bolla, Manjeet K
AU  - Wang, Qin
AU  - Dennis, Joe
AU  - Wilcox, Amber N
AU  - Hopper, John L
AU  - Southey, Melissa C
AU  - Keeman, Renske
AU  - Fasching, Peter A
AU  - Beckmann, Matthias W
AU  - Gago-Dominguez, Manuela
AU  - Castelao, Jose E
AU  - Guénel, Pascal
AU  - Truong, Thérèse
AU  - Bojesen, Stig E
AU  - Flyger, Henrik
AU  - Brenner, Hermann
AU  - Arndt, Volker
AU  - Brauch, Hiltrud
AU  - Brüning, Thomas
AU  - Mannermaa, Arto
AU  - Kosma, Veli-Matti
AU  - Lambrechts, Diether
AU  - Keupers, Machteld
AU  - Couch, Fergus J
AU  - Vachon, Celine
AU  - Giles, Graham G
AU  - MacInnis, Robert J
AU  - Figueroa, Jonine
AU  - Brinton, Louise
AU  - Czene, Kamila
AU  - Brand, Judith S
AU  - Gabrielson, Marike
AU  - Humphreys, Keith
AU  - Cox, Angela
AU  - Cross, Simon S
AU  - Dunning, Alison M
AU  - Orr, Nick
AU  - Swerdlow, Anthony
AU  - Hall, Per
AU  - Pharoah, Paul D P
AU  - Schmidt, Marjanka K
AU  - Easton, Douglas F
AU  - Chatterjee, Nilanjan
AU  - Chang-Claude, Jenny
AU  - García-Closas, Montserrat
TI  - Joint associations of a polygenic risk score and environmental risk factors for breast cancer in the Breast Cancer Association Consortium.
JO  - International journal of epidemiology
VL  - 47
IS  - 2
SN  - 1464-3685
CY  - Oxford
PB  - Oxford Univ. Press
M1  - DKFZ-2018-00557
SP  - 526 - 536
PY  - 2018
AB  - Polygenic risk scores (PRS) for breast cancer can be used to stratify the population into groups at substantially different levels of risk. Combining PRS and environmental risk factors will improve risk prediction; however, integrating PRS into risk prediction models requires evaluation of their joint association with known environmental risk factors.Analyses were based on data from 20 studies; datasets analysed ranged from 3453 to 23 104 invasive breast cancer cases and similar numbers of controls, depending on the analysed environmental risk factor. We evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS with reproductive history, alcohol consumption, menopausal hormone therapy (MHT), height and body mass index (BMI). We tested the null hypothesis of multiplicative joint associations for PRS and each of the environmental factors, and performed global and tail-based goodness-of-fit tests in logistic regression models. The outcomes were breast cancer overall and by estrogen receptor (ER) status.The strongest evidence for a non-multiplicative joint associations with the 77-SNP PRS was for alcohol consumption (P-interaction = 0.009), adult height (P-interaction = 0.025) and current use of combined MHT (P-interaction = 0.038) in ER-positive disease. Risk associations for these factors by percentiles of PRS did not follow a clear dose-response. In addition, global and tail-based goodness of fit tests showed little evidence for departures from a multiplicative risk model, with alcohol consumption showing the strongest evidence for ER-positive disease (P = 0.013 for global and 0.18 for tail-based tests).The combined effects of the 77-SNP PRS and environmental risk factors for breast cancer are generally well described by a multiplicative model. Larger studies are required to confirm possible departures from the multiplicative model for individual risk factors, and assess models specific for ER-negative disease.
LB  - PUB:(DE-HGF)16
C6  - pmid:29315403
C2  - pmc:PMC5913605
DO  - DOI:10.1093/ije/dyx242
UR  - https://inrepo02.dkfz.de/record/132915
ER  -