Structural brain magnetic resonance imaging of pediatric twins

Abstract

To explore the relative impact of genetic and nongenetics factors on human brain anatomy during childhood and adolescence development, a collaborative team from the Child Psychiatry Branch of the National Institute of Mental Health and Virginia Commonwealth University is applying structural equation modeling to brain morphometric data acquired via magnetic resonance imaging from a large sample of monozygotic and dizygotic pediatric subjects. In this report, we discuss methodologic issues related to pediatric neuroimaging twin studies and synthesize results to date from the project. Current sample size from the ongoing longitudinal study is approximately 150 twin pairs. Consistent themes are: (1) heritability is high and shared environmental effects low for most brain morphometric measures; (2) the cerebellum has a distinct heritability profile; (3) genetic and environmental factors contribute to the development of the cortex in a regional and age specific manner; and (4) shared genetic effects account for more of the variance than structure specific effects. Understanding of influences on trajectories of brain development may shed light on the emergence of psychopathology during childhood and adolescence and ultimately may guide therapeutic interventions.

Figure 1

Path diagram depicting the classical ACE model for univariate variance component analysis. With MZ and DZ twins, three latent variables can be identified representing an additive genetic factor (A), a shared environmental factor (C) and a unique environmental factor (E). Paths depict the strength of the relationship between latent factors and the observed phenotype and are analogous to beta weights in linear regression. α represents the genetic correlation between twins (1 for MZ pairs, Â1/2 for DZ pairs). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

Figure 2

The extended twin design. [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]

Figure 3

Examples of extensions into multivariate analyses. For simplicity, only one member of a twin pair is shown in each model. A: Univariate analyses run in parallel with four observed variables. There is no covariance between phenotypes. B: Cholesky decomposition, with only genetic factors shown. The triple Cholesky would include a series of C and E factors with the same pattern as A. C: Independent pathways model. D: Common pathways model. The influences of A, C, and E are mediated through common, latent phenotypes (LP). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]