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.
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.
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DOI：
10.1186/bcr2797
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Chang-Claude J
中科院分区：
文献类型：
--
作者：
Milne RL;Gaudet MM;Spurdle AB;Fasching PA;Couch FJ;Benítez J;Arias Pérez JI;Zamora MP;Malats N;Dos Santos Silva I;Gibson LJ;Fletcher O;Johnson N;Anton-Culver H;Ziogas A;Figueroa J;Brinton L;Sherman ME;Lissowska J;Hopper JL;Dite GS;Apicella C;Southey MC;Sigurdson AJ;Linet MS;Schonfeld SJ;Freedman DM;Mannermaa A;Kosma VM;Kataja V;Auvinen P;Andrulis IL;Glendon G;Knight JA;Weerasooriya N;Cox A;Reed MW;Cross SS;Dunning AM;Ahmed S;Shah M;Brauch H;Ko YD;Brüning T;GENICA Network;Lambrechts D;Reumers J;Smeets A;Wang-Gohrke S;Hall P;Czene K;Liu J;Irwanto AK;Chenevix-Trench G;Holland H;kConFab;AOCS;Giles GG;Baglietto L;Severi G;Bojensen SE;Nordestgaard BG;Flyger H;John EM;West DW;Whittemore AS;Vachon C;Olson JE;Fredericksen Z;Kosel M;Hein R;Vrieling A;Flesch-Janys D;Heinz J;Beckmann MW;Heusinger K;Ekici AB;Haeberle L;Humphreys MK;Morrison J;Easton DF;Pharoah PD;García-Closas M;Goode EL;Chang-Claude J
最近发现了几种常见的乳腺癌遗传易感性变异。我们的目标是通过参加乳腺癌协会联合会的病例对照研究，确定这些变异如何与其他已知风险因素的子集相结合，影响欧洲血统的白人女性的乳腺癌风险。我们评估了12个单核苷酸多态(SNP)(10q26-rs2981582(FGFR2)、8q24-rs13281615、11p15-rs3817198(LSP1)、5q11-rs889312(MAP3K1)、16q12-rs3803662(TOX3)、2q35-rs13387042、5p12-rs10941679(MRPS30)、17q23-rs6504950(COX11)、324-rs4973768(SLC4A7)、CASP8-rs174687、27q12-rs3803662(TOX3)、2q35-rs13387042、5p12-rs10941679(MRPS30)、17q23-rs6504950(COX11)、324-rs4973768(SLC4A7)、CASP8-rs174687、27g12-rs3803662(TOX3)、2q35-rs13387042、5p12-rs10941679(MRPS30)、17q23-rs6504950(COX11)、324-rs4973768(SLC4A7)、CASP8-rs174687、27g12-rs3803662(TOX3)、2q35-rs13387042、5p12-rs10941679(MRPS30)、17q23-rs6504950(COX11)、324-rs4973768(SLC4A7)、CASP8-rs174687、27g12-rs3803662(TOX3)、2q35-rs13387042、5p12交互作用通过拟合Logistic回归模型进行检验，该模型包括SNPs和危险因素的每等位基因和线性趋势主效应，以及线性偏离独立乘法效应的单参数交互作用项。这些分析应用于来自21个病例对照研究的多达26,349例浸润性乳腺癌病例和多达32,208名对照的数据。除了偶然的预期之外，没有观察到相互作用的统计证据。使用11项基于人群的研究数据重复分析，结果非常相似。到目前为止，与常见易感变异相关的乳腺癌相对风险在不同生育史或身体质量指数(BMI)的女性中似乎没有变化。在风险预测模型中，这些已建立的遗传和其他风险因素的乘法组合效应的假设似乎是合理的。
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.
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1.9
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