E12 Abnormal Cortico-striatal Structural Connectivity In Premanifest Huntington's Disease

Abstract

Background Huntington’s disease (HD) is a genetic condition that affects both the white and grey matter of the brain. One of the structures most affected by HD is the basal ganglia, which shows significant atrophy prior to disease manifestation. Using voxel connectivity maps we investigate differences in the patterns of cortical connectivity of the striatum in premanifest HD compared to controls. Aims Our aim was to detect differences in patterns of cortico-striatal structural connectivity between premanifest HD and controls using voxel connectivity maps obtained by diffusion tractography. Methods The cohort consists of 16 pre-manifest HD participants (8 female; mean age 42.20 ± 8.15 years; mean CAG repeat length 43.06 ± 2.01) and 18 controls (6 female; mean age 49.13 ± 8.09 years). Participants underwent MRI scanning and diffusion weighted and T1 images were obtained. Following this constrained spherical deconvolution reconstruction and probabilistic tractography were performed and voxel connectivity maps generated. Each voxel in the striatum was allowed to connect to multiple cortical targets. Classical canonical variate analysis, a multivariate technique, was then used to compare the patterns of connectivity between groups. Results Significant between group differences are seen in the structural connectivity to cortical regions of the right caudate (p = 0.034), right globus pallidum (p = 0.022) and left putamen (p = 0.036). Lateral orbitofrontal, pars triangularis and paracentral regions predominantly account for these differences in the caudate and putamen. In the globus pallidum group differences are observed in frontal, temporal, parietal and occipital connexions. Conclusions In this work we show a method that is sensitive enough to detect differences in patterns of connectivity between controls and pre-manifest HD patients. In future work, we aim to apply this methodology to a larger cohort and correlate connectivity patterns with several clinical scores.