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Multivariate genetic analysis of brain structure in an extended twin design.

机译:扩展双胞胎设计中大脑结构的多元遗传分析。

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摘要

The hunt for genes influencing behavior may be aided by the study of intermediate phenotypes for several reasons. First, intermediate phenotypes may be influenced by only a few genes, which facilitates their detection. Second, many intermediate phenotypes can be measured on a continuous quantitative scale and thus can be assessed in affected and unaffected individuals. Continuous measures increase the statistical power to detect genetic effects (Neale et al., 1994), and allow studies to be designed to collect data from informative subjects such as extreme concordant or discordant pairs. Intermediate phenotypes for discrete traits, such as psychiatric disorders, can be neurotransmitter levels, brain function, or structure. In this paper we conduct a multivariate analysis of data from 111 twin pairs and 34 additional siblings on cerebellar volume, intracranial space, and body height. The analysis is carried out on the raw data and specifies a model for the mean and the covariance structure. Results suggest that cerebellar volume and intracranial space vary with age and sex. Brain volumes tend to decrease slightly with age, and males generally have a larger brain volume than females. The remaining phenotypic variance of cerebellar volume is largely genetic (88%). These genetic factors partly overlap with the genetic factors that explain variance in intracranial space and body height. The applied method is presented as a general approach for the analysis of intermediate phenotypes in which the effects of correlated variables on the observed scores are modeled through multivariate analysis.
机译:出于多种原因,研究中间表型可能有助于寻找影响行为的基因。首先,中间表型可能仅受少数基因的影响,这有利于它们的检测。其次,许多中间表型可以在连续的定量范围内进行测量,因此可以在受影响和未受影响的个体中进行评估。连续的测量增加了检测遗传效应的统计能力(Neale et al。,1994),并允许设计研究以从信息对象(如极端一致或不一致的对)中收集数据。离散性状(例如精神疾病)的中间表型可以是神经递质水平,脑功能或结构。在本文中,我们对来自111对双胞胎和34个其他同胞的小脑容量,颅内空间和身高进行了数据多变量分析。分析是对原始数据进行的,并指定了均值和协方差结构的模型。结果表明,小脑体积和颅内空间随年龄和性别而变化。脑容量往往随着年龄的增长而略有下降,男性通常比女性大。小脑体积的其余表型变异很大程度上是遗传的(88%)。这些遗传因素与解释颅内空间和身高差异的遗传因素部分重叠。提出的应用方法是分析中间表型的通用方法,在该方法中,相关变量对观察分数的影响是通过多变量分析建模的。

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