Conflict of interest statement: No conflicts declared.
A pediatric twin study of brain morphometry
Article first published online: 26 OCT 2006
Journal of Child Psychology and Psychiatry
Volume 47, Issue 10, pages 987–993, November 2006
How to Cite
Wallace, G. L., Eric Schmitt, J., Lenroot, R., Viding, E., Ordaz, S., Rosenthal, M. A., Molloy, E. A., Clasen, L. S., Kendler, K. S., Neale, M. C. and Giedd, J. N. (2006), A pediatric twin study of brain morphometry. Journal of Child Psychology and Psychiatry, 47: 987–993. doi: 10.1111/j.1469-7610.2006.01676.x
- Issue published online: 26 OCT 2006
- Article first published online: 26 OCT 2006
- Manuscript accepted 4 May 2006
- Brain development;
- brain imaging;
- behavioral genetics
Background: Longitudinal pediatric neuroimaging studies have demonstrated increasing volumes of white matter and regionally-specific inverted U shaped developmental trajectories of gray matter volumes during childhood and adolescence. Studies of monozygotic and dyzygotic twins during this developmental period allow exploration of genetic and non-genetic influences on these developmental trajectories.
Method: Magnetic resonance imaging brain scans were acquired on a pediatric sample of 90 monozygotic twin pairs, 38 same-sex dyzygotic twin pairs, and 158 unrelated typically developing singletons. Structural equation modeling was used to estimate the additive genetic, common environment, and unique environment effects, as well as age by heritability interactions, on measures of brain volumes from these images.
Results: Consistent with previous adult studies, additive genetic effects accounted for a substantial portion of variability in nearly all brain regions with the notable exception of the cerebellum. Significant age by heritability interactions were observed with gray matter volumes showing a reduction in heritability with increasing age, while white matter volume heritability increased with greater age.
Conclusion: Understanding the relative contributions of genetic and nongenetic factors on developmental brain trajectories may have implications for better understanding brain-based disorders and typical cognitive development.