Multivariate genetic analysis of brain structure in an extended twin design.
paper
Cited
Public
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- Authors
- Posthuma, D; de Geus, E J; Neale, M C; Hulshoff Pol, H E; BaarΓ© WEC; Kahn, R S; Boomsma, D
- Year
- 2000
- Journal
- Behavior genetics
- PMID
- 11206086
- DOI
- 10.1023/a:1026501501434
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.
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