Structural model analysis of multiple quantitative traits.
Structural model analysis of multiple quantitative traits.
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DOI：
10.1371/journal.pgen.0020114
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发表时间：
2006-07
期刊：
影响因子：
4.5
通讯作者：
Churchill GA
中科院分区：
文献类型：
--
作者：
Li R;Tsaih SW;Shockley K;Stylianou IM;Wergedal J;Paigen B;Churchill GA
我们介绍了一种多位点，多性状的遗传数据，提供了一个直观和精确的遗传结构表征的分析方法。我们表明，它是可能的，以推断多个相关的表型之间的因果关系的大小和方向，并说明该技术使用的身体成分和骨密度数据从小鼠杂交种群。使用这些技术，我们能够区分影响肥胖的遗传位点和影响整体体型的遗传位点，从而揭示了肥胖研究中广泛使用的标准化测量方法（如体重指数）的缺点。因果网络的识别揭示了复杂遗传系统中遗传异质性和多效性的本质。疾病状态通常与可能由共享的遗传和非遗传因素导致的多个相关性状相关。多个性状的遗传分析可以揭示一个效应网络，其中每个性状受到一个以上的遗传位点的影响（异质性），不同的性状共享一个或多个共同的基因座（多效性）。独立于遗传因素的生理相互作用也可能有助于观察到的相关性。结构方程模型是一种描述多性状遗传系统结构的统计方法。应用结构方程模型的身体大小，肥胖，和骨骼几何特征说明了如何影响的遗传位点可以分解沿着直接和间接的路径，可能是通过与其他性状的相互作用介导。使用这种技术，作者确定了肥胖位点，其作用独立于影响整体体型的位点。
We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems. Disease states are often associated with multiple, correlated traits that may result from shared genetic and nongenetic factors. Genetic analysis of multiple traits can reveal a network of effects in which each trait is influenced by more than one genetic locus (heterogeneity) and different traits share one or more loci in common (pleiotropy). Physiological interactions independent of genetic factors may also contribute to the observed correlations. Structural equation modeling is proposed as a statistical method to characterize the architecture of multiple trait genetic systems. Application of structural equation modeling to body size, adiposity, and bone geometry traits illustrates how the effects of a genetic locus can be decomposed along direct and indirect paths that may be mediated through interactions with other traits. Using this technique the authors identify adiposity loci that act independently of loci affecting overall body size.
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