Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer
Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer
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DOI：
10.1086/321276
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发表时间：
2001-07-01
影响因子：
9.8
通讯作者：
Moore, JH
中科院分区：
文献类型：
--
作者：
Ritchie, MD;Hahn, LW;Moore, JH
人类遗传学家面临的最大挑战之一是对常见复杂多因素人类疾病的易感基因进行鉴定和表征。这一挑战部分是由于参数统计方法在检测仅或部分依赖于与其他基因以及环境暴露相互作用的基因效应方面存在局限性。我们引入多因子降维（MDR）作为一种降低多位点信息维度的方法，以改进对与疾病风险相关的多态性组合的鉴定。MDR方法是非参数的（即，不针对统计参数的值做出假设），是无模型的（即，不假定特定的遗传模型），并且直接适用于病例 - 对照和不一致同胞对研究。利用模拟的病例 - 对照数据，我们证明MDR在相对较小的样本中具有合理的能力来识别两个或多个位点之间的相互作用。当将其应用于散发性乳腺癌病例 - 对照数据集时，在没有任何具有统计学意义的独立主效应的情况下，MDR在来自三个不同雌激素代谢基因的四个多态性之间鉴定出具有统计学意义的高阶相互作用。据我们所知，这是首次报道与一种常见复杂多因素疾病相关的四位点相互作用。
One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease.