Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population-based study in Ontario.
Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population-based study in Ontario.
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DOI：
10.1186/1741-7015-5-22
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发表时间：
2007-08-07
期刊：
影响因子：
9.3
通讯作者：
Ozcelik H
中科院分区：
文献类型：
--
作者：
Briollais L;Wang Y;Rajendram I;Onay V;Shi E;Knight J;Ozcelik H
越来越多的证据表明，基因-基因相互作用在决定对人类常见疾病的易感性方面是普遍存在的。由于基因组中潜在相互作用的数量可能很大，对这种基因-基因相互作用的研究对样本量相对较小的研究提出了新的统计挑战。乳腺癌为研究遗传复杂疾病提供了一个有用的范例，因为常见的单核苷酸多态性（snp）可能会累加或协同地干扰导致癌症发展的细胞过程的全系统通信。在这项研究中，我们系统地研究了来自安大略省398例乳腺癌病例和372例对照的18个主要癌症通路关键基因的19个snp之间的SNP-SNP相互作用。我们通过应用和比较三种常用的方法来讨论与该数据集中SNP-SNP相互作用检测相关的方法学问题：逻辑回归模型、分类和回归树（CART）和多因素降维（MDR）方法。我们的分析显示了与乳腺癌相关的几种简单（双向）和复杂（多路）SNP-SNP相互作用的证据。例如，三种方法均鉴定出XPD-[Lys751Gln]*IL10-[G(-1082)A]为最显著的双向相互作用。CART和MDR发现了参与复杂相互作用的相同关键snp。我们的结果表明，使用多种统计方法（或综合方法）而不是单一方法可能是阐明具有通常非常不同模式的复杂基因相互作用的最佳策略。这里使用的策略有可能确定乳腺癌基因和过程之间复杂的生物学关系。这将导致新的生物学信息的发现，这将改善乳腺癌的风险管理。
There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs) may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development. In this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART), and the multifactor dimensionality reduction (MDR) method. Our analyses show evidence for several simple (two-way) and complex (multi-way) SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082)A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach) rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns. The strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.
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影响因子：
10.4
作者：
Au, William W;Salama, Salama A;Sierra-Torres, Carlos H
通讯作者：
Sierra-Torres, Carlos H
影响因子：
2
作者：
Friedman, JH;Meulman, JJ
通讯作者：
Meulman, JJ
DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
BENJAMINI, Y;HOCHBERG, Y
通讯作者：
HOCHBERG, Y
影响因子：
5.8
作者：
Hahn, LW;Ritchie, MD;Moore, JH
通讯作者：
Moore, JH
影响因子：
4.5
作者：
FRIEDMAN, JH
通讯作者：
FRIEDMAN, JH