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Background Although global brain structure is highly heritable, there is still variability in the magnitude of genetic influences on the size of specific regions. Yet, little is known about the patterning of those genetic influences, i.e., whether the same genes influence structure throughout the brain or whether there are regionally-specific sets of genes. Methods We mapped the heritability of cortical thickness throughout the brain using 3D structural magnetic resonance imaging in 404 middle-aged male twins. To assess the amount of genetic overlap between regions, we then mapped genetic correlations between three selected seed points and all other points comprising the continuous cortical surface. Results There was considerable regional variability in the magnitude of genetic influences on cortical thickness. The primary visual (V1) seed point had strong genetic correlations with posterior sensory and motor areas. The anterior temporal seed point had strong genetic correlations with anterior frontal regions, but not with V1. The middle frontal seed point had strong genetic correlations with inferior parietal regions. Conclusions These results provide strong evidence of regionally-specific patterns rather than a single, global genetic factor. The patterns are largely consistent with a division between primary and association cortex, as well as broadly-defined patterns of brain gene expression, neuroanatomical connectivity, and brain maturation trajectories, but no single explanation appears to be sufficient. The patterns do not conform to traditionally-defined brain structure boundaries. This approach can serve as a step toward identifying novel phenotypes for genetic association studies of psychiatric disorders, and normal and pathological cognitive aging.

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The gene MECP2 is a well-known determinant of brain structure. Mutations in the MECP2 protein cause microencephalopathy and are associated with several neurodevelopmental disorders that affect both brain morphology and cognition. Although mutations in MECP2 result in severe neurological phenotypes, the effect of common variation in this genetic region is unknown. We find that common sequence variations in a region in and around MECP2 show association with structural brain size measures in 2 independent cohorts, a discovery sample from the Thematic Organized Psychosis research group, and a replication sample from the Alzheimer's Disease Neuroimaging Initiative. The most statistically significant replicated association (P < 0.025 in both cohorts) involved the minor allele of SNP rs2239464 with reduced cortical surface area, and the finding was specific to male gender in both populations. Variations in the MECP2 region were associated with cortical surface area but not cortical thickness. Secondary analysis showed that this allele was also associated with reduced surface area in specific cortical regions (cuneus, fusiform gyrus, pars triangularis) in both populations.MRI ͉ neuroscience ͉ imaging genetics

Cortical surface area is an increasingly used brain morphology metric that is ontogenetically and phylogenetically distinct from cortical thickness and offers a separate index of neurodevelopment and disease. However, the various existing methods for assessment of cortical surface area from magnetic resonance images have never been systematically compared. We show that the surface area method implemented in FreeSurfer corresponds closely to the exact, but computationally more demanding, mass-conservative (pycnophylactic) method, provided that images are smoothed. Thus, the data produced by this method can be interpreted as estimates of cortical surface area, as opposed to areal expansion. In addition, focusing on the joint analysis of thickness and area, we compare an improved, analytic method for measuring cortical volume to a permutation-based nonparametric combination (NPC) method. We use the methods to analyze area, thickness and volume in young adults born preterm with very low birth weight, and show that NPC analysis is a more sensitive option for studying joint effects on area and thickness, giving equal weight to variation in both of these 2 morphological features.

Loss-of-function mutations in the genes associated with primary microcephaly (MCPH) reduce human brain size by about twothirds, without producing gross abnormalities in brain organization or physiology and leaving other organs largely unaffected [Woods CG, et al. (2005) Am J Hum Genet 76:717-728]. There is also evidence suggesting that MCPH genes have evolved rapidly in primates and humans and have been subjected to selection in recent human evolution [Vallender EJ, et al. (2008) Trends Neurosci 31:637-644]. Here, we show that common variants of MCPH genes account for some of the common variation in brain structure in humans, independently of disease status. We investigated the correlations of SNPs from four MCPH genes with brain morphometry phenotypes obtained with MRI. We found significant, sex-specific associations between common, nonexonic, SNPs of the genes CDK5RAP2, MCPH1, and ASPM, with brain volume or cortical surface area in an ethnically homogenous Norwegian discovery sample (n = 287), including patients with mental illness. The most strongly associated SNP findings were replicated in an independent North American sample (n = 656), which included patients with dementia. These results are consistent with the view that common variation in brain structure is associated with genetic variants located in nonexonic, presumably regulatory, regions.

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