Barrdahl Myrto, Canzian Federico, Joshi Amit D, Travis Ruth C, Chang-Claude Jenny, Auer Paul L, Gapstur Susan M, Gaudet Mia, Diver W Ryan, Henderson Brian E, Haiman Christopher A, Schumacher Fredrick R, Le Marchand Loïc, Berg Christine D, Chanock Stephen J, Hoover Robert N, Rudolph Anja, Ziegler Regina G, Giles Graham G, Baglietto Laura, Severi Gianluca, Hankinson Susan E, Lindström Sara, Willet Walter, Hunter David J, Buring Julie E, Lee I-Min, Zhang Shumin, Dossus Laure, Cox David G, Khaw Kay-Tee, Lund Eiliv, Naccarati Alessio, Peeters Petra H, Quirós J Ramón, Riboli Elio, Sund Malin, Trichopoulos Dimitrios, Prentice Ross L, Kraft Peter, Kaaks Rudolf, Campa Daniele
Division of Cancer Epidemiology and.
Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg D-69120, Germany.
Hum Mol Genet. 2014 Oct 1;23(19):5260-70. doi: 10.1093/hmg/ddu223. Epub 2014 May 8.
We studied the interplay between 39 breast cancer (BC) risk SNPs and established BC risk (body mass index, height, age at menarche, parity, age at menopause, smoking, alcohol and family history of BC) and prognostic factors (TNM stage, tumor grade, tumor size, age at diagnosis, estrogen receptor status and progesterone receptor status) as joint determinants of BC risk. We used a nested case-control design within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), with 16 285 BC cases and 19 376 controls. We performed stratified analyses for both the risk and prognostic factors, testing for heterogeneity for the risk factors, and case-case comparisons for differential associations of polymorphisms by subgroups of the prognostic factors. We analyzed multiplicative interactions between the SNPs and the risk factors. Finally, we also performed a meta-analysis of the interaction ORs from BPC3 and the Breast Cancer Association Consortium. After correction for multiple testing, no significant interaction between the SNPs and the established risk factors in the BPC3 study was found. The meta-analysis showed a suggestive interaction between smoking status and SLC4A7-rs4973768 (Pinteraction = 8.84 × 10(-4)) which, although not significant after considering multiple comparison, has a plausible biological explanation. In conclusion, in this study of up to almost 79 000 women we can conclusively exclude any novel major interactions between genome-wide association studies hits and the epidemiologic risk factors taken into consideration, but we propose a suggestive interaction between smoking status and SLC4A7-rs4973768 that if further replicated could help our understanding in the etiology of BC.
我们研究了39个乳腺癌(BC)风险单核苷酸多态性(SNP)与既定的BC风险因素(体重指数、身高、初潮年龄、生育情况、绝经年龄、吸烟、饮酒及BC家族史)和预后因素(TNM分期、肿瘤分级、肿瘤大小、诊断时年龄、雌激素受体状态及孕激素受体状态)之间的相互作用,将其作为BC风险的联合决定因素。我们在美国国立癌症研究所的乳腺癌和前列腺癌队列联盟(BPC3)中采用巢式病例对照设计,纳入了16285例BC病例和19376例对照。我们对风险因素和预后因素均进行了分层分析,检验风险因素的异质性,并对预后因素亚组中多态性的差异关联进行病例-病例比较。我们分析了SNP与风险因素之间的相乘相互作用。最后,我们还对来自BPC3和乳腺癌协会联盟的相互作用比值比(OR)进行了荟萃分析。经过多重检验校正后,在BPC3研究中未发现SNP与既定风险因素之间存在显著相互作用。荟萃分析显示吸烟状态与SLC4A7-rs4973768之间存在提示性相互作用(P相互作用 = 8.84×10⁻⁴),尽管在考虑多重比较后不显著,但有合理的生物学解释。总之,在这项针对近79000名女性的研究中,我们可以明确排除全基因组关联研究发现与所考虑的流行病学风险因素之间存在任何新的主要相互作用,但我们提出吸烟状态与SLC4A7-rs4973768之间存在提示性相互作用,若能进一步得到验证,可能有助于我们理解BC的病因。