He Crawford

Evaluation of multi-modal, multi-site neuroimaging measures in Huntington's disease: Baseline results from the PADDINGTON study

Background Macro- and micro-structural neuroimaging measures provide valuable information on the pathophysiology of Huntingtons disease (HD) and are proposed as biomarkers. Despite theoretical advantages of microstructural measures in terms of sensitivity to pathology, there is little evidence directly comparing the two. Methods 40 controls and 61 early HD subjects underwent 3 T MRI (T1- and diffusion-weighted), as part of the PADDINGTON study. Macrostructural volumetrics were obtained for the whole brain, caudate, putamen, corpus callosum (CC) and ventricles. Microstructural diffusion metrics of fractional anisotropy (FA), mean-, radial- and axial-diffusivity (MD, RD, AD) were computed for white matter (WM), CC, caudate and putamen. Group differences were examined adjusting for age, gender and site. A formal comparison of effect sizes determined which modality and metrics provided a statistically significant advantage over others. Results Macrostructural measures showed decreased regional and global volume in HD (p < 0.001); except the ventricles which were enlarged (p < 0.01). In HD, FA was increased in the deep grey-matter structures (p < 0.001), and decreased in the WM (CC, p = 0.035; WM, p = 0.053); diffusivity metrics (MD, RD, AD) were increased for all brain regions (p < 0.001). The largest effect sizes were for putamen volume, caudate volume and putamen diffusivity (AD, RD and MD); each was significantly larger than those for all other metrics (p < 0.05). Conclusion The highest performing macro- and micro-structural metrics had similar sensitivity to HD pathology quantified via effect sizes. Region-of-interest may be more important than imaging modality, with deep grey-matter regions outperforming the CC and global measures, for both volume and diffusivity. FA appears to be relatively insensitive to disease effects.

Corpus Callosal Atrophy in Premanifest and Early Huntington's Disease

BACKGROUND Volumetric MRI studies have highlighted the pronounced loss of white matter in premanifest and early Huntingtons Disease (HD). The current study focussed on the corpus callosum (CC) since it provides interhemispheric connections to vulnerable cortical areas. OBJECTIVES To investigate cross-sectional and longitudinal group differences in CC volume and hypothesis-driven associations with three cognitive tasks. METHODS Baseline and 24-month 3T MRI were analysed from 106 premanifest (PreHD), (59 preHD-A ≥10.8 and 47 preHD-B <10.8 years from predicted onset), 84 early HD (53 Stage 1 (HD1) and 31 Stage 2 (HD2)) and 101 control subjects from the TRACK-HD study, using a semi-automated technique for CC delineation. Between-group differences in volume and 24-month atrophy rates, and correlations with cognitive performance were investigated using regression models, adjusting for potential confounders. RESULTS PreHD-B, HD1 and HD2 had statistically significantly smaller baseline CC volumes (p < 0.001) and all groups had elevated 24-month atrophy rates compared with controls (p < 0.001). Smaller baseline CC volume was associated with impaired performance in the Circle Tracing Indirect task in early HD (p < 0.05). Positive, non-statistically significant relationships with Stroop Word Reading were shown in both gene-positive groups. There was no evidence of an association with the Trail Making B task. CONCLUSIONS We found reduced CC volume and elevated 24-month atrophy rates, even in individuals far from disease onset. Structural degeneration of interhemispheric connections may contribute to cognitive deficits, such as performance in the Circle Tracing Indirect task in HD. Examination of different image acquisitions may provide more specific information about underlying CC degeneration.

Detection of motor changes in huntington's disease using dynamic causal modeling

Deficits in motor functioning are one of the hallmarks of Huntingtons disease (HD), a genetically caused neurodegenerative disorder. We applied functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess changes that occur with disease progression in the neural circuitry of key areas associated with executive and cognitive aspects of motor control. Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD), and 16 patients with manifest HD symptoms (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Wards method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters that also differed significantly between these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.

G01 Evaluation of multi-modal, multi-site imaging measures in Huntington's disease: baseline results from the PADDINGTON study

Background Macro- and micro-structural brain changes are of interest as markers of Huntingtons Disease (HD) progression, which may prove useful in future clinical trials. The relative sensitivity of these markers is unknown. Aims To evaluate macro-structural volume measurements and micro-structural diffusion measurements in HD. Methods 40 controls and 61 early stage HD subjects, recruited across four EU sites, underwent 3T MRI plus a clinical and cognitive battery. Volumetric measurements of the whole brain, caudate, putamen, corpus callosum and ventricles were performed using MIDAS. Diffusion metrics of fractional anisotropy (FA), mean- radial- and axial-diffusivity (MD, RD and AD) were computed over the white matter, corpus callosum, caudate and putamen. Group differences were examined adjusting for age, gender and site. Results Compared with controls, HD subjects showed strong evidence of reduced volume in all brain regions examined (p<0.001), except for the ventricles which were enlarged (p<0.01). The largest volumetric effect sizes were for the putamen (−2.405, 95% CI −2.942 to −1.753) and caudate (−2.346, 95% CI −2.956 to −1.576). All diffusion metrics showed significant differences between controls and HD (p<0.05), with the exception of white-matter FA (p=0.053). The largest diffusion effect sizes were seen in the caudate and putamen diffusivity metrics; putamen AD showed an effect size of 1.882 (95% CI 1.396 to 2.178). Effect sizes tended to be smaller for diffusion metrics than the corresponding volumetrics. A statistical analysis of these differences will be presented. Conclusion Both volumetric and diffusion metrics are sensitive to disease effects in HD. Robust statistical comparison of effect sizes for these measures will help inform the design of future clinical trials. Funding This work has been supported by the European Union – PADDINGTON project, contract n. HEALTH-F2-2010-261358.

Brain Regions Showing White Matter Loss in Huntington's Disease Are Enriched for Synaptic and Metabolic Genes

Background The earliest white matter changes in Huntington’s disease are seen before disease onset in the premanifest stage around the striatum, within the corpus callosum, and in posterior white matter tracts. While experimental evidence suggests that these changes may be related to abnormal gene transcription, we lack an understanding of the biological processes driving this regional vulnerability. Methods Here, we investigate the relationship between regional transcription in the healthy brain, using the Allen Institute for Brain Science transcriptome atlas, and regional white matter connectivity loss at three time points over 24 months in subjects with premanifest Huntington’s disease relative to control participants. The baseline cohort included 72 premanifest Huntington’s disease participants and 85 healthy control participants. Results We show that loss of corticostriatal, interhemispheric, and intrahemispheric white matter connections at baseline and over 24 months in premanifest Huntington’s disease is associated with gene expression profiles enriched for synaptic genes and metabolic genes. Corticostriatal gene expression profiles are predominately associated with motor, parietal, and occipital regions, while interhemispheric expression profiles are associated with frontotemporal regions. We also show that genes with known abnormal transcription in human Huntington’s disease and animal models are overrepresented in synaptic gene expression profiles, but not in metabolic gene expression profiles. Conclusions These findings suggest a dual mechanism of white matter vulnerability in Huntington’s disease, in which abnormal transcription of synaptic genes and metabolic disturbance not related to transcription may drive white matter loss.

Natural biological variation of white matter microstructure is accentuated in Huntington's disease

Huntingtons disease (HD) is a monogenic neurodegenerative disorder caused by a CAG‐repeat expansion in the Huntingtin gene. Presence of this expansion signifies certainty of disease onset, but only partly explains age at which onset occurs. Genome‐wide association studies have shown that naturally occurring genetic variability influences HD pathogenesis and disease onset. Investigating the influence of biological traits in the normal population, such as variability in white matter properties, on HD pathogenesis could provide a complementary approach to understanding disease modification. We have previously shown that while white matter diffusivity patterns in the left sensorimotor network were similar in controls and HD gene‐carriers, they were more extreme in the HD group. We hypothesized that the influence of natural variation in diffusivity on effects of HD pathogenesis on white matter is not limited to the sensorimotor network but extends to cognitive, limbic, and visual networks. Using tractography, we investigated 32 bilateral pathways within HD‐related networks, including motor, cognitive, and limbic, and examined diffusivity metrics using principal components analysis. We identified three independent patterns of diffusivity common to controls and HD gene‐carriers that predicted HD status. The first pattern involved almost all tracts, the second was limited to sensorimotor tracts, and the third encompassed cognitive network tracts. Each diffusivity pattern was associated with network specific performance. The consistency in diffusivity patterns across both groups coupled with their association with disease status and task performance indicates that naturally‐occurring patterns of diffusivity can become accentuated in the presence of the HD gene mutation to influence clinical brain function.

Testing a longitudinal compensation model in premanifest Huntington’s disease

Owing to compensatory processes, the initial stages of neurodegeneration are marked by normal performance despite the presence of pathology. Using their explicit mathematical model, Gregory et al. report the first empirical examination of compensation over time in neurodegeneration, showing evidence of motor and cognitive compensation in a Huntington’s disease cohort.

D16 White matter microstructure and natural biological variation in huntington’s disease

Background The genetic basis of Huntington’s disease (HD) explains much of the heterogeneity in the age of disease onset, but a substantial portion of this variability remains unexplained. In addition to potential environmental and HD-specific genetic modifiers, biological traits already present in the normal population may also influence HD pathogenesis. In a recent study, we identified a pattern of diffusivity in the white matter (WM) of HD participants that was independent of other HD-specific factors and was also present in healthy controls. Aims We used Diffusion Tensor Imaging from the TrackOn-HD study to examine further the role of biological variation in widespread WM tracts in premanifest-HD, early HD and control groups. Methods Tractography was performed for 36 bilateral WM tracts, including connexions between cortical and subcortical regions and sensorimotor-thalamic connexions. Three diffusivity measures (fractional anisotropy, axial diffusivity and radial diffusivity) were assessed using Principal Components Analysis both within and between the three groups. Results We found that three independent patterns of diffusivity distinguished premanifest from manifest HD gene-carriers. Three analogous patterns of diffusivity were also evident in the control group. Exaggerated scores on two of these three patterns correlated with other known biological measures of HD severity, and did not independently predict disease stage. The third, however, was independent of other known HD biology and did predict disease status. Conclusions The overlap in patterns of diffusivity between controls and HD gene-carriers suggests that natural biological variation in the presence of HD-specific factors may influence WM vulnerability to the HD mutation.

G03 Corpus callosal atrophy in Huntington's disease

Background Research into Huntingtons disease (HD) has revealed white-matter loss in individuals more than 10 years prior to predicted disease onset, focused around the striatum, corpus callosum (CC) and posterior white-matter tracts. Degeneration of the CC is of interest since it provides interhemispheric connections to cortical areas known to be affected in HD. Aims This study aims to investigate the utility of volumetric measurements of the CC in HD using a novel segmentation technique, multiple time-points and a large well-characterised cohort. Structure-function relationship in the CC will also be explored. Methods Volumetric 3T MRI from controls, premanifest gene carriers and early HD subjects enrolled in the TRACK-HD study will be analysed at baseline and 24 months. The CC will be delineated using a semi-automated segmentation protocol. Differences in baseline volumes and atrophy rates between groups will be examined, as well as correlations between volume loss and clinical impairment. Results Preliminary analysis of a subset of subjects indicates that early HD subjects have reduced CC volume compared with controls and premanifest subjects (p<0.001). Increased longitudinal CC volume change was found in early HD subjects, compared with controls (p<0.001). Interestingly there was significant difference in longitudinal change between controls and premanifest subjects close to disease onset (p<0.05). This work will be extended to include multi-site data and correlations between atrophy and clinical and cognitive decline. Conclusions Measurement of CC atrophy may have potential as an imaging biomarker for HD and may prove useful for exploring interhemispheric structure-function relationships. Funding Helen Crawford is supported by the CHDI Foundation, a not for profit organisation dedicated to finding treatments for HD.

RELIABILITY OF DIFFUSION TENSOR IMAGING MEASURES

Background Huntingtons disease (HD) has been associated with white matter (WM) abnormalities, evident using diffusion tensor imaging (DTI) analysis. However, the limited longitudinal work in this area has been inconclusive and further research into the progressive WM degeneration in HD is required. A key factor in the validity of results from longitudinal DTI research is the reliability of these measurements, which is not well-established. Aim To assess the test-retest reliability of DTI-based measures of brain structure. Methods Using repeat DTI data from 12 participants scanned at the London and Paris sites of the PADDINGTON study (scan interval range 0–24 days), the reliability of measures derived from different analysis methods was assessed by calculating intra-class correlations coefficients (ICC) for each measure. Results Fractional anisotropy (FA) across the whole brain showed a mean reliability of ICC=0.79. The regional distribution of reliability was also mapped, using voxelwise ICC, with WM regions showing higher ICC compared to grey matter or cerebro-spinal fluid. Tensor-based atlas registration showed substantial variation in reliability between different WM regions, however, assessed across all regions, reliability was high for FA (ICC=0.98) and the trace of diffusivity (ICC=0.98). Using manually delineated regions-of-interest, reliability was high for WM (ICC=0.96) and both the caudate (ICC=0.96) and putamen (ICC=0.97), while corpus callosum reliability was lower (ICC=0.83). Comparable measures of reliability were found for the trace of diffusivity. Conclusions DTI scanning generally produces highly reliable measures of brain structure. There is considerable heterogeneity in reliability between different brain regions and imaging methods. These results will be informative when designing longitudinal research to map progressive brain changes in HD and other degenerative disorders.