A novel method to identify gene-gene effects in nuclear families: The MDR-PDT
A novel method to identify gene-gene effects in nuclear families: The MDR-PDT
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DOI：
10.1002/gepi.20128
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发表时间：
2006-02-01
影响因子：
2.1
通讯作者：
Moore, JH
中科院分区：
文献类型：
--
作者：
Martin, ER;Ritchie, MD;Moore, JH
基因-基因和基因-环境相互作用在复杂疾病中的重要性已被公认，检测相互作用的统计方法也越来越普遍。传统的参数方法在检测高阶相互作用和处理稀疏数据的能力方面受到限制，并且标准逐步过程可能会错过在没有可检测的主效应的情况下发生的相互作用。为了解决这些限制，多因素降维（MDR）方法[里奇等人，2001：Am J Genet 69：138-147]。MDR非常适合于检查高阶交互作用和检测没有主效应的交互作用。MDR最初设计用于分析平衡的病例对照数据。分析可以使用家族数据，但需要从每个家族中选择一个匹配对。这可能是一个不和谐的同胞对，或可能是从三重数据构建时，父母是可用的。为了利用额外的受影响和未受影响的兄弟姐妹，需要一个检验统计量，以衡量基因型与一般核心家庭疾病的关联。我们通过将MDR方法与基因型-谱系不平衡检验（genotype-Pedigree Disequilibrium Test，geno-PDT）合并，开发了一种新的检验，MDR-PDT [Martin et al.，2003：Genet Epidemiol 25：203-213]。MDR-PDT允许在不同结构的家族中鉴定单基因座效应或多基因座的联合效应。我们提出了模拟，以证明测试的有效性，并评估其权力。为了检验其对真实的数据的适用性，我们将MDR-PDT应用于一个大型家族数据集中阿尔茨海默病（AD）候选基因的数据。这些结果显示了MDR-PDT用于理解复杂疾病的遗传学的实用性。
It is now well recognized that gene-gene and gene-environment interactions are important in complex diseases, and statistical methods to detect interactions are becoming widespread. Traditional parametric approaches are limited in their ability to detect high-order interactions and handle sparse data, and standard stepwise procedures may miss interactions that occur in the absence of detectable main effects. To address these limitations, the multifactor dimensionality reduction (MDR) method [Ritchie et al., 2001: Am J Hum Genet 69:138-147] was developed. The MDR is wellsuited for examining high-order interactions and detecting interactions without main effects. The MDR was originally designed to analyze balanced case-control data. The analysis can use family data, but requires a single matched pair be selected from each family. This may be a discordant sib pair, or may be constructed from triad data when parents are available. To take advantage of additional affected and unaffected siblings requires a test statistic that measures the association of genotype with disease in general nuclear families. We have developed a novel test, the MDR-PDT, by merging the MDR method with the genotype-Pedigree Disequilibrium Test (geno-PDT) [Martin et al., 2003: Genet Epidemiol 25:203-213]. MDR-PDT allows identification of single-locus effects or joint effects of multiple loci in families of diverse structure. We present simulations to demonstrate the validity of the test and evaluate its power. To examine its applicability to real data, we applied the MDR-PDT to data from candidate genes for Alzheimer disease (AD) in a large family dataset. These results show the utility of the MDR-PDT for understanding the genetics of complex diseases.