title: Mapping the regional influence of genetics on brain structure variability--a tensor-based morphometry study.
abstract: Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8+/-1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.
authors.affiliation: Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, 635 Charles Young Drive South Suite 225, Los Angeles, CA 90095-7334, USA.
authors.forename: Caroline C
authors.initials: CC
authors.lastname: Brun
authors.forename: Natasha
authors.initials: N
authors.lastname: Leporé
authors.forename: Xavier
authors.initials: X
authors.lastname: Pennec
authors.forename: Agatha D
authors.initials: AD
authors.lastname: Lee
authors.forename: Marina
authors.initials: M
authors.lastname: Barysheva
authors.forename: Sarah K
authors.initials: SK
authors.lastname: Madsen
authors.forename: Christina
authors.initials: C
authors.lastname: Avedissian
authors.forename: Yi-Yu
authors.initials: YY
authors.lastname: Chou
authors.forename: Greig I
authors.initials: GI
authors.lastname: de Zubicaray
authors.forename: Katie L
authors.initials: KL
authors.lastname: McMahon
authors.forename: Margaret J
authors.initials: MJ
authors.lastname: Wright
authors.forename: Arthur W
authors.initials: AW
authors.lastname: Toga
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
mesh_terms: D000328:Adult; D001921:Brain / Q000033:anatomy & histology*; D004777:Environment; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008959:Models, Neurological; D009929:Organ Size; D010641:Phenotype; D017422:Sequence Analysis, DNA; D014429:Twins, Dizygotic; D014430:Twins, Monozygotic; D055815:Young Adult