Anatomic magnetic resonance imaging of the developing child and adolescent brain and effects of genetic variation

Abstract

Magnetic resonance imaging studies have begun to map effects of genetic variation on trajectories of brain development. Longitudinal studies of children and adolescents demonstrate a general pattern of childhood peaks of gray matter followed by adolescent declines, functional and structural increases in connectivity and integrative processing, and a changing balance between limbic/subcortical and frontal lobe functions, which extends well into young adulthood. Twin studies have demonstrated that genetic factors are responsible for a significant amount of variation in pediatric brain morphometry. Longitudinal studies have shown specific genetic polymorphisms affect rates of cortical changes associated with maturation. Although over-interpretation and premature application of neuroimaging findings for diagnostic purposes remains a risk, converging data from multiple imaging modalities is beginning to elucidate the influences of genetic factors on brain development and implications of maturational changes for cognition, emotion, and behavior.

Fig. 1

Scatterplot of longitudinal measurements of total brain volume for males (N=475 scans, shown in dark gray) and females (N=354 scans, shown in light gray) (Lenroot et al. 2007)

Fig. 2

Mean volume by age in years for males (N=475 scans) and females (N=354 scans). Middle lines in each set of three lines represent mean values, and upper and lower lines represent upper and lower 95% confidence intervals. a Total brain volume, b Gray matter volume, c White matter volume, d Lateral ventricle volume, e Mid-sagittal area of the corpus callosum, f Caudate volume (Lenroot et al. 2007)

Fig. 3

Right lateral and top views of the dynamic sequence of GM maturation over the cortical surface. The side bar shows a color representation in units of GM volume (Gogtay et al. 2004)

Fig. 4

Graphic representation of structural equation modeling with genetically informative data

Fig. 5

Heritability at ages 5, 12, and 18 years for superior, inferior, right and left cortical surfaces. Colorbar shows scale of heritability values from 0.0 to 1.0 (Lenroot et al. 2009)

Fig. 6

Vertex maps of areas showing statistically significant differences in the rate of cortical thinning between genotype groups. Pheu607Leu top panel, Ser704Cys bottom panel. Phe carriers (PheCar) showed a significant attenuation of cortical thinning relative to Leu homozygotes (LeuLeu) in the colored regions shown. The inset plot illustrates estimated genotype group trajectories for the left superior frontal focus. Ser homozygotes (SerSer) showed a significant acceleration of cortical thinning in the colored regions shown. The inset plot illustrates estimated genotype group trajectories for the left posterior superior temporal focus. In all instances ‘Warmer’ colors indicate thickness trajectory differences of greater statistical significance (Raznahan et al. 2010)