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Wiley InterScience

Journal of Child Psychology and Psychiatry

Journal of Child Psychology and Psychiatry

Volume 47 Issue 10, Pages 987 - 993

Published Online: 26 Oct 2006

Journal Compilation © 2010 ACAMH



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A pediatric twin study of brain morphometry
Gregory L. Wallace 1 , J. Eric Schmitt 2 , Rhoshel Lenroot 1 , Essi Viding 3 , Sarah Ordaz 1 , Michael A. Rosenthal 1 , Elizabeth A. Molloy 4 , Liv S. Clasen 1 , Kenneth S. Kendler 2 , Michael C. Neale 2 , Jay N. Giedd 1
  1 Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, USA ;   2 Virginia Institute for Psychiatric and Behavioral Genetics and Departments of Psychiatry and Human Genetics, Virginia Commonwealth University, Richmond, VA, USA ;   3 Social, Genetic, & Developmental Psychiatry Centre, Institute of Psychiatry, London, UK ;   4 George Washington University School of Medicine, Washington, DC, USA
Correspondence to Jay N. Giedd, Child Psychiatry Branch, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, 20892, USA; Email: jg@nih.gov
 

Conflict of interest statement: No conflicts declared.

Copyright 2006 The Authors Journal compilation 2006 Association for Child and Adolescent Mental Health
KEYWORDS
Brain development • brain imaging • pediatric • twin • behavioral genetics

ABSTRACT

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.


Manuscript accepted 4 May 2006

DIGITAL OBJECT IDENTIFIER (DOI)
10.1111/j.1469-7610.2006.01676.x About DOI

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