Insufficient evidence exists to guide the long-term pharmacological management of Huntington’s disease (HD) although most current interventions rely on symptomatic management. The effect of many frontline treatments on potential endpoints for HD clinical trials remains unknown. Our objective was to investigate how therapies widely used to manage HD affect the symptom for which they are prescribed and other endpoints using data from TRACK-HD. We used longitudinal models to estimate effects of medication use on performance on tests of motor, cognitive and neuropsychiatric function using data from 123 TRACK-HD stage 1/2 participants across four study visits. Adjustment for confounding by prior medication use, prior clinical performance, concomitant use of other medications, and baseline variables (sex, disease group, age, CAG, study site, education) enabled a closer-to-causal interpretation of the associations. Adjusting for baseline variables only, medication use was typically associated with worse clinical performance, reflecting greater medication use in more advanced patients. After additional adjustment for longitudinal confounders such “inverse” associations were generally eliminated and in the expected directions: participants taking neuroleptics tended to have better motor performance, improved affect and poorer cognitive performance, and those taking SSRI/SNRIs had less apathy, less affect and better total behaviour scores. However, we uncovered few statistically significant associations. Limitations include sample size and unmeasured confounding. In conclusion, adjustment for confounding by prior measurements largely eliminated associations between medication use and poorer clinical performance from simple analyses. However, there was little convincing evidence of causal effects of medication on clinical performance and larger cohorts or trials are needed.
In diffusion tensor imaging (DTI), an improvement in the signal-to-noise ratio (SNR) of the fractional anisotropy (FA) maps can be obtained when the number of recorded gradient directions (GD) is increased. Vice versa, elimination of motion-corrupted or noisy GD leads to a more accurate characterization of the diffusion tensor. We previously suggest a slice-wise method for artifact detection in FA maps. This current study applies this approach to a cohort of 18 premanifest Huntington’s disease (pHD) subjects and 23 controls. By 2-D voxelwise statistical comparison of original FA-maps and FA-maps with a reduced number of GD, the effect of eliminating GD that were affected by motion was demonstrated.
We present an evaluation metric that allows to test if the computed FA-maps (with a reduced number of GD) still reflect a “true” FA-map, as defined by simulations in the control sample. Furthermore, we investigated if omitting data volumes affected by motion in the pHD cohort could lead to an increased SNR in the resulting FA-maps.
A high agreement between original FA maps (with all GD) and corrected FA maps (i.e. without GD corrupted by motion) were observed even for numbers of eliminated GD up to 13. Even in one data set in which 46 GD had to be eliminated, the results showed a moderate agreement.
Several candidate modifier genes which, in addition to the pathogenic CAG repeat expansion, influence the age at onset (AO) in Huntington disease (HD) have already been described. The aim of this study was to replicate association of variations in the N-methyl D-aspartate receptor subtype genes GRIN2A and GRIN2B in the “REGISTRY” cohort from the European Huntington Disease Network (EHDN). The analyses did replicate the association reported between the GRIN2A rs2650427 variation and AO in the entire cohort. Yet, when subjects were stratified by AO subtypes, we found nominally significant evidence for an association of the GRIN2A rs1969060 variation and the GRIN2B rs1806201 variation. These findings further implicate the N-methyl D-aspartate receptor subtype genes as loci containing variation associated with AO in HD.
Movement artifacts and other sources of noise are a matter of concern particularly in the neuroimaging research of movement disorders such as Huntington’s disease (HD). Using diffusion weighted imaging (DWI) and fractional anisotropy (FA) as a compound marker of white matter integrity, we investigated the effect of movement on HD specific changes in magnetic resonance imaging (MRI) data and how post hoc compensation for it affects the MRI results. To this end, we studied by 3T MRI: 18 early affected, 22 premanifest gene-positive subjects, 23 healthy controls (50 slices of 2.3 mm thickness per volume, 64 diffusion-weighted directions (b = 1000 s/mm2), 8 minimal diffusion-weighting (b = 100 s/mm2)); and by 1.5 T imaging: 29 premanifest HD, 30 controls (40 axial slices of 2.3 mm thickness per volume, 61 diffusion-weighted directions (b = 1000 s/mm2), minimal diffusion-weighting (b = 100 s/mm2)). An outlier based method was developed to identify movement and other sources of noise by comparing the index DWI direction against a weighted average computed from all other directions of the same subject. No significant differences were observed when separately comparing each group of patients with and without removal of DWI volumes that contained artifacts. In line with previous DWI-based studies, decreased FA in the corpus callosum and increased FA around the basal ganglia were observed when premanifest mutation carriers and early affected patients were compared with healthy controls. These findings demonstrate the robustness of the FA value in the presence of movement and thus encourage multi-center imaging studies in HD.
Huntington’s disease (HD) is an inherited neurodegenerative disorder characterized by both neurological and systemic abnormalities. Immune activation is a well-established feature of the HD brain and we have previously demonstrated a widespread, progressive innate immune response detectable in plasma throughout the course of HD. In the present work we used multiplex ELISA to quantify levels of chemokines in plasma from controls and subjects at different stages of HD. We found an altered chemokine profile tracking with disease progression, with significant elevations of five chemokines (eotaxin-3, MIP-1β, eotaxin, MCP-1 and MCP-4) while three (eotaxin-3, MIP-1β and eotaxin) showed significant linear increases across advancing disease stages. We validated our results in a separate sample cohort including subjects at different stages of HD. Here we saw that chemokine levels (MCP-1 and eotaxin) correlated with clinical scores. We conclude that, like cytokines, chemokines may be linked to the pathogenesis of HD, and that immune molecules may be valuable in tracking and exploring the pathogenesis of HD.
Background: Huntington’s disease (HD) is a rare triplet repeat (CAG) disorder. Advanced, multi-centre, multi-national research frameworks are needed to study simultaneously multiple complementary aspects of HD. This includes the natural history of HD, its management and the collection of clinical information and biosamples for research.
Methods: We report on cross-sectional data of the first 1766 participants in REGISTRY, the European Huntington’s Disease Network’s (EHDN), multi-lingual, multi-national prospective observational study of HD in Europe. Data collection (demographics, phenotype, genotype, medication, co-morbidities, biosamples) followed a standard protocol.
Results: Phenotype, and the HD genotype, of manifest HD participants across different European regions was similar. Motor onset was most common (48%) with a non-motor onset in more than a third of participants. Motor signs increased, and cognitive abilities and functional capacity declined as the disease burden (CAGn-35.5) X age) increased. A life-time history of behavioural symptoms was common, but the behavioural score was not related to disease burden. One fifth of participants had severe psychiatric problems, e.g. suicidal ideation and attempts, and/or irritability/aggression, with psychosis being less common. Participants on anti-dyskinetic medication had a higher motor and lower cognitive score, were older, and more prone to physical trauma. A higher motor and a lower cognitive score predicted more advanced disease.
Conclusions: The unparalleled collection of clinical data and biomaterials within the EHDN’s REGISTRY can expedite the search for disease modifiers (genetic and environmental) of age at onset and disease progression that could be harnessed for the development of novel treatments.