Investigating brain connectivity heritability in a twin study using diffusion imaging data

Abstract

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test–retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.

Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints

“…As illustrated in our analysis of twins, the similarity in monozygotic twins was around twice as much of the dizygotic twins, whereas our post-hoc analysis did not find significant similarity difference between dizygotic twins and non-twins siblings. These results are highly suggestive that genetics contribute a substantial portion to the overall construction of the local connectome, which is consistent with previous studies showing high heritability in cortical connections [30, 31] and white matter integrity [32–35]. Nevertheless, our results also showed that the monozygotic twins shared only 12.51% similarity in local white matter architecture.…”

The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects

“…A large proportion (40-80%) of the intersubject variance in the DTI-FA values(Braskie et al, 2011; Chiang et al, 2012; Chiang et al, 2009; Jahanshad et al, 2012; Jahanshad et al, 2010; Kochunov et al, 2015; Shen et al, 2014) and processing speed measurements(Glahn et al, 2011; Glahn et al, 2013) is explained by additive genetic factors. The high degree of genetic influence of these two traits posits them as important endophenotypes for genetic search for risk factors for heritable psychiatric disorders such as schizophrenia that are associated with both DTI-FA and processing speed deficits.…”

784. Structural Dysconnectivity of Key Cognitive and Emotional Hubs in Young People at High Genetic Risk for Bipolar Disorder

“…CN subjects were recruited via print and electronic media, and noticeboards in universities and local communities. Sample ascertainment and separate clinical assessments for younger (15)(16)(17)(18)(19)(20)(21) and older (22)(23)(24)(25)(26)(27)(28)(29)(30) age categories are provided in Perich et al 36 and in Supplementary Information 1.1. We pooled data across both age cohorts unless there was a specific correlation between a brain network measure and an age-specific clinical variable in either group.…”

“…15 Given the strong heritability of WM morphology, 16,17 studying individuals at familial risk of developing BD may help identify neurobiological factors that pre-empt the development of BD, as well as factors associated with resilience. This objective is particularly pertinent in young first-degree relatives who have not yet passed the peak age of illness onset.…”