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

Progressive alterations in white matter microstructure across the timecourse of Huntington's disease

BACKGROUND

Whole-brain longitudinal diffusion studies are crucial to examine changes in structural connectivity in neurodegeneration. Here, we investigated the longitudinal alterations in white matter (WM) microstructure across the timecourse of Huntington's disease (HD).

METHODS

We examined changes in WM microstructure from premanifest to early manifest disease, using data from two cohorts with different disease burden. The TrackOn-HD study included 67 controls, 67 premanifest, and 10 early manifest HD (baseline and 24-month data); the PADDINGTON study included 33 controls and 49 early manifest HD (baseline and 15-month data). Longitudinal changes in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, and radial diffusivity from baseline to last study visit were investigated for each cohort using tract-based spatial statistics. An optimized pipeline was employed to generate participant-specific templates to which diffusion tensor imaging maps were registered and change maps were calculated. We examined longitudinal differences between HD expansion-carriers and controls, and correlations with clinical scores, including the composite UHDRS (cUHDRS).

RESULTS

HD expansion-carriers from TrackOn-HD, with lower disease burden, showed a significant longitudinal decline in FA in the left superior longitudinal fasciculus and an increase in MD across subcortical WM tracts compared to controls, while in manifest HD participants from PADDINGTON, there were significant widespread longitudinal increases in diffusivity compared to controls. Baseline scores in clinical scales including the cUHDRS predicted WM microstructural change in HD expansion-carriers.

CONCLUSION

The present study showed significant longitudinal changes in WM microstructure across the HD timecourse. Changes were evident in larger WM areas and across more metrics as the disease advanced, suggesting a progressive alteration of WM microstructure with disease evolution.

Investigating longitudinal changes to frontal cortico-striatal tracts in Huntington's disease: the IMAGE-HD study

The striatum is the principal site of disease pathology in Huntington's disease and contains neural connections to numerous cortical brain regions. Studies examining abnormalities to neural connections find that white matter integrity is compromised in HD; however, further regional, and longitudinal investigation is required. This paper is the first longitudinal investigation into region-based white-matter integrity changes in Huntington's Disease. The aim of this study was to better understand how disease progression impacts white matter tracts connecting the striatum to the prefrontal and motor cortical regions in HD. We used existing neuroimaging data from IMAGE-HD, comprised of 25 pre-symptomatic, 27 symptomatic, and 25 healthy controls at three separate time points (baseline, 18-months, 30-months). Fractional anisotropy, axial diffusivity and radial diffusivity were derived as measures of white matter microstructure. The anatomical regions of interest were identified using the Desikan-Killiany brain atlas. A Group by Time repeated measures ANCOVA was conducted for each tract of interest and for each measure. We found significantly lower fractional anisotropy and significantly higher radial diffusivity in the symptomatic group, compared to both the pre-symptomatic group and controls (the latter two groups did not differ from each other), in the rostral middle frontal and superior frontal tracts; as well as significantly higher axial diffusivity in the rostral middle tracts only. We did not find a Group by Time interaction for any of the white matter integrity measures. These findings demonstrate that whilst the microstructure of white matter tracts, extending from the striatum to these regions of interest, are compromised during the symptomatic stages of Huntington's disease, 36-month follow-up did not show progressive changes in these measures. Additionally, no correlations were found between clinical measures and tractography changes, indicating further investigations into the relationship between tractography changes and clinical symptoms in Huntington's disease are required.

Early and progressive dysfunction revealed by in vivo neurite imaging in the rNLS8 TDP-43 mouse model of ALS

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Are neurite density and dispersion altered in amyotropic lateral sclerosis (ALS)?

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Both measures are affected in the rNLS8 TDP-43 mouse model of ALS.

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Diffusion tensor imaging metrics were also affected.

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Group-wise changes were observed early in the disease course.

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Together these diffusion imaging metrics may aid in the timelier diagnosis of ALS.

Amyotrophic lateral sclerosis (ALS) is characterized by transactive response DNA-binding protein 43 (TDP-43) pathology, progressive loss of motor neurons and muscle dysfunction. Symptom onset can be insidious and diagnosis challenging. Conventional neuroimaging is used to exclude ALS mimics, however more advanced neuroimaging techniques may facilitate an earlier diagnosis. Here, we investigate the potential for neurite orientation dispersion and density imaging and diffusion tensor imaging (DTI) to detect microstructural changes in an experimental model of ALS with neuronal doxycycline (Dox)-suppressible overexpression of human TDP-43 (hTDP-43). In vivo diffusion-weighted imaging (DWI) was acquired 1- and 3- weeks following the initiation of hTDP-43 expression (post-Dox) to investigate whether neurite density imaging (NDI) and orientation dispersion imaging (ODI) are affected early in this preclinical model of ALS and if so, how these metrics compare to those derived from the diffusion tensor. Tract-based spatial statistics at 1-week post-Dox, i.e. very early in the disease stage, demonstrated increased NDI in TDP-43 mice but no change in ODI or DTI metrics. At 3-weeks post-Dox, a reduced pattern of increased NDI was observed along with widespread increases in ODI, and decreased fractional anisotropy (FA), apparent diffusion coefficient (ADC) and axial diffusivity (AD). A hypothesis driven analysis of the bilateral corticospinal tracts demonstrated that at 1-week post-Dox, ODI was significantly increased caudally but decreased in the motor cortex of TDP-43 mice. Decreased cortical ODI had normalized by 3-weeks post-Dox and only significant increases were observed. A similar, but inverse pattern in FA was also observed. Together, these results suggest a non-monotonic relationship between DWI metrics and pathophysiological progression with TDP-43 mice exhibiting significantly altered diffusion metrics consistent with early inflammation followed by progressive axonal degeneration. Importantly, significant group-wise changes were observed in the earliest stages of disease when subtle pathology may be more elusive to traditional structural imaging techniques.

Classification of Huntington's Disease Stage with Features Derived from Structural and Diffusion-Weighted Imaging

The purpose of this study was to classify Huntington’s disease (HD) stage using support vector machines and measures derived from T1- and diffusion-weighted imaging. The effects of feature selection approach and combination of imaging modalities are assessed. Fourteen premanifest-HD individuals (Pre-HD; on average > 20 years from estimated disease onset), eleven early-manifest HD (Early-HD) patients, and eighteen healthy controls (HC) participated in the study. We compared three feature selection approaches: (i) whole-brain segmented grey matter (GM; voxel-based measure) or fractional anisotropy (FA) values; (ii) GM or FA values from subcortical regions-of-interest (caudate, putamen, pallidum); and (iii) automated selection of GM or FA values with the algorithm Relief-F. We assessed single- and multi-kernel approaches to classify combined GM and FA measures. Significant classifications were achieved between Early-HD and Pre-HD or HC individuals (accuracy: generally, 85% to 95%), and between Pre-HD and controls for the feature FA of the caudate ROI (74% accuracy). The combination of GM and FA measures did not result in higher performances. We demonstrate evidence on the high sensitivity of FA for the classification of the earliest Pre-HD stages, and successful distinction between HD stages.

Validating Automated Segmentation Tools in the Assessment of Caudate Atrophy in Huntington's Disease

Background: Neuroimaging shows considerable promise in generating sensitive and objective outcome measures for therapeutic trials across a range of neurodegenerative conditions. For volumetric measures the current gold standard is manual delineation, which is unfeasible for samples sizes required for large clinical trials. Methods: Using a cohort of early Huntington's disease (HD) patients (n = 46) and controls (n = 35), we compared the performance of four automated segmentation tools (FIRST, FreeSurfer, STEPS, MALP-EM) with manual delineation for generating cross-sectional caudate volume, a region known to be vulnerable in HD. We then examined the effect of each of these baseline regions on the ability to detect change over 15 months using the established longitudinal Caudate Boundary Shift Integral (cBSI) method, an automated longitudinal pipeline requiring a baseline caudate region as an input. Results: All tools, except Freesurfer, generated significantly smaller caudate volumes than the manually derived regions. Jaccard indices showed poorer levels of overlap between each automated segmentation and manual delineation in the HD patients compared with controls. Nevertheless, each method was able to demonstrate significant group differences in volume (p < 0.001). STEPS performed best qualitatively as well as quantitively in the baseline analysis. Caudate atrophy measures generated by the cBSI using automated baseline regions were largely consistent with those derived from a manually segmented baseline, with STEPS providing the most robust cBSI values across both control and HD groups. Conclusions: Atrophy measures from the cBSI were relatively robust to differences in baseline segmentation technique, suggesting that fully automated pipelines could be used to generate outcome measures for clinical trials.

Diffusion Tensor Imaging in Preclinical and Human Studies of Huntington's Disease: What Have we Learned so Far?

BACKGROUND

Huntington's Disease is an irreversible neurodegenerative disease characterized by the progressive deterioration of specific brain nerve cells. The current evaluation of cellular and physiological events in patients with HD relies on the development of transgenic animal models. To explore such events in vivo, diffusion tensor imaging has been developed to examine the early macro and microstructural changes in brain tissue. However, the gap in diffusion tensor imaging findings between animal models and clinical studies and the lack of microstructural confirmation by histological methods has questioned the validity of this method.

OBJECTIVE

This review explores white and grey matter ultrastructural changes associated to diffusion tensor imaging, as well as similarities and differences between preclinical and clinical Huntington's Disease studies.

METHODS

A comprehensive review of the literature using online-resources was performed (Pub- Med search).

RESULTS

Similar changes in fractional anisotropy as well as axial, radial and mean diffusivities were observed in white matter tracts across clinical and animal studies. However, comparative diffusion alterations in different grey matter structures were inconsistent between clinical and animal studies.

CONCLUSION

Diffusion tensor imaging can be related to specific structural anomalies in specific cellular populations. However, some differences between animal and clinical studies could derive from the contrasting neuroanatomy or connectivity across species. Such differences should be considered before generalizing preclinical results into the clinical practice. Moreover, current limitations of this technique to accurately represent complex multicellular events at the single micro scale are real. Future work applying complex diffusion models should be considered.

Diffusion imaging in Huntington's disease: comprehensive review

Huntington's disease (HD) is a monogenic disorder with 100% penetrance. With the advent of genetic testing in adults, disease-related, structural brain changes can be investigated from the earliest, premorbid stages of HD. While examining macrostructural change characterises global neuronal damage, investigating microstructural alterations provides information regarding brain organisation and its underlying biological properties. Diffusion MRI can be used to track the progression of microstructural anomalies in HD decades prior to clinical disease onset, providing a greater understanding of neurodegeneration. Multiple approaches, including voxelwise, region of interest and tractography, have been used in HD cohorts, showing a centrifugal pattern of white matter (WM) degeneration starting from deep brain areas, which is consistent with neuropathological studies. The corpus callosum, longer WM tracts and areas that are more densely connected, in particular the sensorimotor network, also tend to be affected early during premanifest stages. Recent evidence supports the routine inclusion of diffusion analyses within clinical trials principally as an additional measure to improve understanding of treatment effects, while the advent of novel techniques such as multitissue compartment models and connectomics can help characterise the underpinnings of progressive functional decline in HD.

Longitudinal atrophy characterization of cortical and subcortical gray matter in Huntington's disease patients

Huntington's disease (HD) is an inherited neurodegenerative disease with clinical manifestations that involve motor, cognitive and psychiatric deficits. Cross-sectional magnetic resonance imaging (MRI) studies have described the main cortical and subcortical macrostructural atrophy of HD. However, longitudinal studies characterizing progressive atrophy are lacking. This study aimed to describe the cortical and subcortical gray matter atrophy using complementary volumetric and surface-based MRI analyses in a cohort of seventeen early HD patients in a cross-sectional and longitudinal analysis and to correlate the longitudinal volumetric atrophy with the functional decline using several clinical measures. A group of seventeen healthy individuals was included as controls. After obtaining structural MRIs, volumetric analyses were performed in 36 cortical and 7 subcortical regions of interest per hemisphere and surface-based analyses were performed in the whole cortex, caudate, putamen and thalamus. Cross-sectional cortical surface-based and volumetric analyses showed significant decreases in frontoparietal and temporo-occipital cortices, while subcortical volumetric analysis showed significant decreases in all subcortical structures except the hippocampus. The longitudinal surface-based analysis showed widespread cortical thinning with volumetric decreases in the superior frontal lobe, while a subcortical volumetric decrease occurred in the caudate, putamen and thalamus with shape deformation on the anterior, medial and dorsal side. Functional capacity and motor status decline correlated with caudate progressive atrophy, while cognitive decline correlated with left superior frontal and right paracentral progressive atrophy. These results provide new insights into progressive volumetric and surface-based morphometric atrophy of gray matter in HD.

Fluid and imaging biomarkers for Huntington's disease

Huntington's disease is a chronic progressive neurodegenerative condition for which there is no disease-modifying treatment. The known genetic cause of Huntington's disease makes it possible to identify individuals destined to develop the disease and instigate treatments before the onset of symptoms. Multiple trials are already underway that target the cause of HD, yet clinical measures are often insensitive to change over typical clinical trial duration. Robust biomarkers of drug target engagement, disease severity and progression are required to evaluate the efficacy of treatments and concerted efforts are underway to achieve this. Biofluid biomarkers have potential advantages of direct quantification of biological processes at the molecular level, whilst imaging biomarkers can quantify related changes at a structural level in the brain. The most robust biofluid and imaging biomarkers can offer complementary information, providing a more comprehensive evaluation of disease stage and progression to inform clinical trial design and endpoints.

Combined cerebral atrophy score in Huntington's disease based on atlas-based MRI volumetry: Sample size calculations for clinical trials

INTRODUCTION

A volumetric MRI analysis of longitudinal regional cerebral atrophy in Huntington's disease (HD) was performed as a read-out of disease progression to calculate sample sizes for future clinical trials.

METHODS

This study was based on MRI data of 59 patients with HD and 40 controls recruited within the framework of the PADDINGTON study and investigated at baseline and follow-up after 6 and 15 months. Automatic atlas-based volumetry (ABV) of structural T1-weighted scans was used to calculate longitudinal volume changes of brain structures relevant in HD and to assess standardized effect sizes and sample sizes required for potential future studies.

RESULTS

Atrophy rates were largest in the caudate (-3.4%), putamen (-2.8%), nucleus accumbens (-1.6%), and the parietal lobes (-1.7%); the lateral ventricles showed an expansion by 6.0%. Corresponding effect sizes were -1.35 (caudate), -0.84 (putamen), -0.91 (nucleus accumbens), -1.05 (parietal lobe), and 0.92 (lateral ventricles) leading to N = 36 subjects per study group for detecting a 50% attenuation of atrophy for the best performing structure (caudate). A combined score of volume changes in non-overlapping compartments (striatum, parietal lobes, lateral ventricles) increased the effect size to -1.60 and substantially reduced the required sample sizes by 10 to N = 26 subjects per study group. This combined imaging score correlated significantly both with the CAP score and with the progression of the clinical phenotype.

CONCLUSION

We propose ABV of the striatum together with parietal lobe and lateral ventricle volumes as a combined imaging read-out for progression studies including clinical trials in HD.

Translating Antisense Technology into a Treatment for Huntington's Disease

Advances in molecular biology and genetics have been used to elucidate the fundamental genetic mechanisms underlying central nervous system (CNS) diseases, yet disease-modifying therapies are currently unavailable for most CNS conditions. Antisense oligonucleotides (ASOs) are synthetic single stranded chains of nucleic acids that bind to a specific sequence on ribonucleic acid (RNA) and regulate posttranscriptional gene expression. Decreased gene expression with ASOs might be able to reduce production of the disease-causing protein underlying dominantly inherited neurodegenerative disorders. Huntington's disease (HD), which is caused by a CAG repeat expansion in exon 1 of the huntingtin (HTT) gene and leads to the pathogenic expansion of a polyglutamine (PolyQ ) tract in the N terminus of the huntingtin protein (Htt), is a prime candidate for ASO therapy.State-of-the art translational science techniques can be applied to the development of an ASO targeting HTT RNA, allowing for a data-driven, stepwise progression through the drug development process. A deep and wide-ranging understanding of the basic, preclinical, clinical, and epidemiologic components of drug development will improve the likelihood of success. This includes characterizing the natural history of the disease, including evolution of biomarkers indexing the underlying pathology; using predictive preclinical models to assess the putative gain-of-function of mutant Htt protein and any loss-of-function of the wild-type protein; characterizing toxicokinetic and pharmacodynamic effects of ASOs in predictive animal models; developing sensitive and reliable biomarkers to monitor target engagement and effects on pathology that translate from animal models to patients with HD; establishing a drug delivery method that ensures reliable distribution to relevant CNS tissue; and designing clinical trials that move expeditiously from proof of concept to proof of efficacy. This review focuses on the translational science techniques that allow for efficient and informed development of an ASO for the treatment of HD.

Scan-rescan repeatability and cross-scanner comparability of DTI metrics in healthy subjects in the SPRINT-MS multicenter trial

PURPOSE

To assess intrascanner repeatability and cross-scanner comparability for diffusion tensor imaging (DTI) metrics in a multicenter clinical trial.

METHODS

DTI metrics (including longitudinal diffusivity [LD], fractional anisotropy [FA], mean diffusivity [MD], and transverse diffusivity [TD]) from pyramidal tracts for healthy controls were calculated from images acquired on twenty-seven 3T MR scanners (Siemens and GE) with 6 different scanner models and 7 different software versions as part of the NN102/SPRINT-MS clinical trial. Each volunteer underwent two scanning sessions on the same scanner. Signal-to-noise ratio (SNR) and signal-to-noise floor ratio (SNFR) were also assessed.

RESULTS

DTI metrics showed good scan-rescan repeatability. There were no significant differences between scans and rescans in LD, FA, MD, or TD values. Although the cross-scanner coefficient of variation (CV) values for all DTI metrics were <5.7%, significant differences were observed for LD (p < 3.3e-5) and FA (p < 0.0024) when GE scanners were compared with Siemens scanners. Significant differences were also observed for SNR when comparing GE scanners and Siemens Skyra scanners (p < 1.4e-7) and when comparing Siemens Skyra scanners and TIM Trio scanners (p < 1.0e-10). Analysis of background signal also demonstrated differences between GE and Siemens scanners in terms of signal statistics. The measured signal intensity from a background noise region of interest was significantly higher for GE scanners than for Siemens scanners (p < 1.2e-12). Significant differences were also observed for SNFR when comparing GE scanners and Siemens Skyra scanners (p < 2.5e-11), GE scanners and Siemens Trio scanners (p < 7.5e-11), and Siemens Skyra scanners and TIM Trio scanners (p < 2.5e-9).

CONCLUSIONS

The good repeatability of the DTI metrics among the 27 scanners used in this study confirms the feasibility of combining DTI data from multiple centers using high angular resolution sequences. Our observations support the feasibility of longitudinal multicenter clinical trials using DTI outcome measures. The noise floor level and SNFR are important parameters that must be assessed when comparing studies that used different scanner models.

An image-based model of brain volume biomarker changes in Huntington's disease

Objective

Determining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine‐grained model of temporal progression of Huntington's disease from premanifest through to manifest stages.

Methods

We employ a probabilistic event‐based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track‐HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides.

Results

The model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross‐validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow‐up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers.

Interpretation

We used a data‐driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event‐based model, to provide new insight into Huntington's disease progression and to support fine‐grained patient stratification for future precision medicine in Huntington's disease.

Quantification of huntingtin protein species in Huntington's disease patient leukocytes using optimised electrochemiluminescence immunoassays

BACKGROUND

Huntington's disease (HD) is an autosomal dominant neurodegenerative condition caused by an expanded CAG repeat in the gene encoding huntingtin (HTT). Optimizing peripheral quantification of huntingtin throughout the course of HD is valuable not only to illuminate the natural history and pathogenesis of disease, but also to detect peripheral effects of drugs in clinical trial.

RATIONALE

We previously demonstrated that mutant HTT (mHTT) was significantly elevated in purified HD patient leukocytes compared with controls and that these levels track disease progression. Our present study investigates whether the same result can be achieved with a simpler and more scalable collection technique that is more suitable for clinical trials.

METHODS

We collected whole blood at 133 patient visits in two sample sets and generated peripheral blood mononuclear cells (PBMCs). Levels of mHTT, as well as N-, and C-terminal and mid-region huntingtin were measured in the PBMCs using ELISA-based Meso Scale Discovery (MSD) electrochemiluminescence immunoassay platforms, and we evaluated the relationship between different HTT species, disease stage, and brain atrophy on magnetic resonance imaging.

CONCLUSIONS

The assays were sensitive and accurate. We confirm our previous findings that mHTT increases with advancing disease stage in patient PBMCs, this time using a simple collection protocol and scalable assay.

Structural imaging in premanifest and manifest Huntington disease

Huntington disease (HD) neuropathology has a devastating effect on brain structure and consequently brain function; neuroimaging provides a means to assess these effects in gene carriers. In this chapter we first outline the unique utility of structural imaging in understanding HD and discuss some of the acquisition and analysis techniques currently available. We review the existing literature to summarize what we know so far about structural brain changes across the spectrum of disease from premanifest through to manifest disease. We then consider how these neuroimaging findings relate to patient function and nonimaging biomarkers, and can be used to predict disease onset. Finally we review the utility of imaging measures for assessment of treatment efficacy in clinical trials.

Diffusion imaging studies of Huntington's disease: A meta-analysis

BACKGROUND

Diffusion tensor imaging (DTI) could detect abnormal brain microstructural alterations. DTI studies of Huntington's Disease(HD) have yielded inconsistent results.

OBJECTIVE

To integrate the existing DTI studies of HD and explore the validity of DTI to detect microstructural damages in HD brain via meta-analysis.

METHODS

Systematic and comprehensive searches of the databases were performed for DTI studies of HD. The data from the studies that met our inclusion criteria were extracted and analyzed using the CMA2 software. Random effect models were utilized to minimize the potential between-study heterogeneity. One-way sensitivity analysis was conducted to test the robustness of the results.

RESULTS

The meta-analysis included 140 pre-symptomatic HD (PreHD), 235 symptomatic HD (SymHD) patients and 302 controls, revealing significantly increased fractional anisotropy (FA) in the caudate, putamen, and globus pallidus, while decreased FA in the corpus callosum of both PreHD and SymHD patients compared with controls. In addition, significantly increased mean diffusivity (MD) was identified in the putamen and thalamus of both PreHD and SymHD patients, and in the caudate of SymHD patients, while no significant difference in MD in the caudate of PreHD patients. In the corpus callosum, there was a significant increase of radial diffusivity and axial diffusivity in SymHD patients compared with controls. Meta-regression showed gender-based difference in MD values of the caudate.

CONCLUSIONS

Our meta-analysis provides further evidence that DTI detects microstructural damage of both white matter and gray matter even in PreHD gene carriers. MD is less sensitive than FA in detecting structural changes in PreHD.

A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis

OBJECTIVE

Damage to the cerebral tissue structural connectivity associated with amyotrophic lateral sclerosis (ALS), which extends beyond the motor pathways, can be visualised by diffusion tensor imaging (DTI). The effective translation of DTI metrics as biomarker requires its application across multiple MRI scanners and patient cohorts. A multicentre study was undertaken to assess structural connectivity in ALS within a large sample size.

METHODS

442 DTI data sets from patients with ALS (N=253) and controls (N=189) were collected for this retrospective study, from eight international ALS-specialist clinic sites. Equipment and DTI protocols varied across the centres. Fractional anisotropy (FA) maps of the control participants were used to establish correction matrices to pool data, and correction algorithms were applied to the FA maps of the control and ALS patient groups.

RESULTS

Analysis of data pooled from all centres, using whole-brain-based statistical analysis of FA maps, confirmed the most significant alterations in the corticospinal tracts, and captured additional significant white matter tract changes in the frontal lobe, brainstem and hippocampal regions of the ALS group that coincided with postmortem neuropathological stages. Stratification of the ALS group for disease severity (ALS functional rating scale) confirmed these findings.

INTERPRETATION

This large-scale study overcomes the challenges associated with processing and analysis of multiplatform, multicentre DTI data, and effectively demonstrates the anatomical fingerprint patterns of changes in a DTI metric that reflect distinct ALS disease stages. This success paves the way for the use of DTI-based metrics as read-out in natural history, prognostic stratification and multisite disease-modifying studies in ALS.

Participants at the Leiden Site of the REGISTRY Study: A Demographic Approach

BACKGROUND

REGISTRY is the largest European observational study of Huntington's disease (HD). The Leiden University Medical Center (LUMC) in The Netherlands is the largest recruiting site.

OBJECTIVE

The aim of this paper is to give an overview of the baseline characteristics of all Leiden participants from the start of the study in 2005 until the close of REGISTRY at the LUMC in September 2014.

METHODS

The Leiden cohort is described in two different ways: CAG repeat length and presence of motor signs.

RESULTS

Division into groups based on prolonged CAG length revealed that the cohort consists of 4 intermediate - (27-35 CAG), 22 reduced penetrance - (36-39 CAG), 465 full penetrance - (>39 CAG) and 60 control participants (<27 CAG). The second way of dividing the participants based on present or absent of motor signs, showed that 170 pre-motormanifest - and 317 motormanifest participants were enrolled.

CONCLUSION

The Leiden REGISTRY cohort at baseline is mainly characterized by full penetrance gene expansion carriers who have been clinically diagnosed with HD but who remain relatively functionally independent. For the majority of these participants, disease onset was based on motor signs followed by psychiatric and cognitive signs.

Large-scale brain network abnormalities in Huntington's disease revealed by structural covariance

Huntington's disease (HD) is a progressive neurodegenerative disorder that can be diagnosed with certainty decades before symptom onset. Studies using structural MRI have identified grey matter (GM) loss predominantly in the striatum, but also involving various cortical areas. So far, voxel-based morphometric studies have examined each brain region in isolation and are thus unable to assess the changes in the interrelation of brain regions. Here, we examined the structural covariance in GM volumes in pre-specified motor, working memory, cognitive flexibility, and social-affective networks in 99 patients with manifest HD (mHD), 106 presymptomatic gene mutation carriers (pre-HD), and 108 healthy controls (HC). After correction for global differences in brain volume, we found that increased GM volume in one region was associated with increased GM volume in another. When statistically comparing the groups, no differences between HC and pre-HD were observed, but increased positive correlations were evident for mHD, relative to pre-HD and HC. These findings could be explained by a HD-related neuronal loss heterogeneously affecting the examined network at the pre-HD stage, which starts to dominate structural covariance globally at the manifest stage. Follow-up analyses identified structural connections between frontoparietal motor regions to be linearly modified by disease burden score (DBS). Moderator effects of disease load burden became significant at a DBS level typically associated with the onset of unequivocal HD motor signs. Together with existing findings from functional connectivity analyses, our data indicates a critical role of these frontoparietal regions for the onset of HD motor signs.

Detection of Motor Changes in Huntington's Disease Using Dynamic Causal Modeling

Deficits in motor functioning are one of the hallmarks of Huntington's 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 Ward's 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.

Dynamics of the connectome in Huntington's disease: A longitudinal diffusion MRI study

Objectives

To longitudinally investigate the connectome in different stages of Huntington's disease (HD) by applying graph theoretical analysis to diffusion MRI data.

Experimental design

We constructed weighted structural networks and calculated their topological properties. Twenty-two premanifest (preHD), 10 early manifest HD and 24 healthy controls completed baseline and 2 year follow-up scans. We stratified the preHD group based on their predicted years to disease onset into a far (preHD-A) and near (preHD-B) to disease onset group. We collected clinical and behavioural measures per assessment time point.

Principle observations

We found a significant reduction over time in nodal betweenness centrality both in the early manifest HD and preHD-B groups as compared to the preHD-A and control groups, suggesting a decrease of importance of specific nodes to overall network organization in these groups (FDR adjusted ps < 0.05). Additionally, we found a significant longitudinal decrease of the clustering coefficient in preHD when compared to healthy controls (FDR adjusted p < 0.05), which can be interpreted as a reduced capacity for internodal information processing at the local level. Furthermore, we demonstrated dynamic changes to hub-status loss and gain both in preHD and early manifest HD. Finally, we found significant cross-sectional as well as longitudinal relationships between graph metrics and clinical and neurocognitive measures.

Conclusions

This study demonstrates divergent longitudinal changes to the connectome in (pre) HD compared to healthy controls. This provides novel insights into structural correlates associated with clinical and cognitive functions in HD and possible compensatory mechanisms at play in preHD.

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Investigates characteristics of the connectome in Huntington's disease (HD).

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HD patients showed longitudinal changes in their structural connectome.

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Connectome dynamics correlated with changes in clinical and cognitive measures.

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Connectomics provides novel insights into compensatory strategies of the diseased brain.

Huntington disease

Huntington disease is devastating to patients and their families - with autosomal dominant inheritance, onset typically in the prime of adult life, progressive course, and a combination of motor, cognitive and behavioural features. The disease is caused by an expanded CAG trinucleotide repeat (of variable length) in HTT, the gene that encodes the protein huntingtin. In mutation carriers, huntingtin is produced with abnormally long polyglutamine sequences that confer toxic gains of function and predispose the protein to fragmentation, resulting in neuronal dysfunction and death. In this Primer, we review the epidemiology of Huntington disease, noting that prevalence is higher than previously thought, geographically variable and increasing. We describe the relationship between CAG repeat length and clinical phenotype, as well as the concept of genetic modifiers of the disease. We discuss normal huntingtin protein function, evidence for differential toxicity of mutant huntingtin variants, theories of huntingtin aggregation and the many different mechanisms of Huntington disease pathogenesis. We describe the genetic and clinical diagnosis of the condition, its clinical assessment and the multidisciplinary management of symptoms, given the absence of effective disease-modifying therapies. We review past and present clinical trials and therapeutic strategies under investigation, including impending trials of targeted huntingtin-lowering drugs and the progress in development of biomarkers that will support the next generation of trials. For an illustrated summary of this Primer, visit: http://go.nature.com/hPMENh.

Microstructural brain abnormalities in Huntington's disease: A two-year follow-up

OBJECTIVES

To investigate both cross-sectional and time-related changes of striatal and whole-brain microstructural properties in different stages of Huntington's disease (HD) using diffusion tensor imaging.

EXPERIMENTAL DESIGN

From the TRACK-HD study, premanifest gene carriers (preHD), early manifest HD and controls were scanned at baseline and 2-year follow-up. Stratification of the preHD group into a far (preHD-A) and near (preHD-B) to predicted disease onset was performed. Age-corrected histograms of whole-brain white matter (WM), gray matter (GM) and striatal diffusion measures were computed and normalised by the number of voxels in each subject's data set.

PRINCIPLE OBSERVATIONS

Higher cross-sectional mean, axial and radial diffusivities were found in both WM (P ≤ 0.001) and GM (P ≤ 0.001) of the manifest HD compared to the preHD and control groups. In preHD, only WM axial diffusivity (AD) was higher than in controls (P ≤ 0.01). This finding remained valid only in preHD-B (P ≤ 0.001). AD was also higher in the striatum of preHD-B compared to controls and preHD-A (P ≤ 0.01). Fractional anisotropy (FA) lacked sensitivity in differentiating between the groups. Histogram peak heights were generally lower in manifest HD compared to the preHD and control groups. No longitudinal differences were found in the degree of diffusivity change between the groups in the two year follow-up. There was a significant relationship between diffusivity and neurocognitive measures.

CONCLUSIONS

Alterations in cross-sectional diffusion profiles between manifest HD subjects and controls were evident, both in whole-brain and striatum. In the preHD stage, only AD alterations were found, a finding suggesting that this metric is a sensitive marker for early change in HD prior to disease manifestation. The individual diffusivities were superior to FA in revealing pathologic microstructural brain alterations. Diffusion measures were well related to clinical functioning and disease stage.

Cerebellar abnormalities in Huntington's disease: a role in motor and psychiatric impairment?

The cerebellum has received limited attention in Huntington's disease (HD), despite signs of possible cerebellar dysfunction, including motor incoordination and impaired gait, which are currently attributed to basal ganglia atrophy and disrupted fronto-striatal circuits. This study is the first to investigate a potential contribution of macro- and microstructural cerebellar damage to clinical manifestations of HD. T1- and diffusion-weighted 3T magnetic resonance imaging (MRI) scans were obtained from 12 controls and 22 early-stage HD participants. Manual delineation and voxel-based morphometry were used to assess between-group differences in cerebellar volume, and diffusion metrics were compared between groups within the cerebellar gray and white matter. Associations between these imaging measures and clinical scores were examined within the HD group. Reduced paravermal volume was detected in HD compared with controls using voxel-based morphometry (P < 0.05), but no significant volumetric differences were found using manual delineation. Diffusion abnormalities were detected in both cerebellar gray matter and white matter. Smaller cerebellar volumes, although not significantly reduced, were significantly associated with impaired gait and psychiatric morbidity and of borderline significance with pronate/supinate-hand task performance. Abnormal cerebellar diffusion was associated with increased total motor score, impaired saccade initiation, tandem walking, and timed finger tapping. In conclusion, atrophy of the paravermis, possibly encompassing the cerebellar nuclei, and microstructural abnormalities within the cerebellum may contribute to HD neuropathology. Aberrant cerebellar diffusion and reduced cerebellar volume together associate with impaired motor function and increased psychiatric symptoms in stage I HD, potentially implicating the cerebellum more centrally in HD presentation than previously recognized.

Test-Retest Reliability of Diffusion Tensor Imaging in Huntington's Disease

Diffusion tensor imaging (DTI) has shown microstructural abnormalities in patients with Huntington's Disease (HD) and work is underway to characterise how these abnormalities change with disease progression. Using methods that will be applied in longitudinal research, we sought to establish the reliability of DTI in early HD patients and controls. Test-retest reliability, quantified using the intraclass correlation coefficient (ICC), was assessed using region-of-interest (ROI)-based white matter atlas and voxelwise approaches on repeat scan data from 22 participants (10 early HD, 12 controls). T1 data was used to generate further ROIs for analysis in a reduced sample of 18 participants. The results suggest that fractional anisotropy (FA) and other diffusivity metrics are generally highly reliable, with ICCs indicating considerably lower within-subject compared to between-subject variability in both HD patients and controls. Where ICC was low, particularly for the diffusivity measures in the caudate and putamen, this was partly influenced by outliers. The analysis suggests that the specific DTI methods used here are appropriate for cross-sectional research in HD, and give confidence that they can also be applied longitudinally, although this requires further investigation. An important caveat for DTI studies is that test-retest reliability may not be evenly distributed throughout the brain whereby highly anisotropic white matter regions tended to show lower relative within-subject variability than other white or grey matter regions.

Biomarker development for Huntington's disease

Huntington's disease (HD) is a fatal inherited neurodegenerative disorder, treatment to slow the progression of which has not yet been found. Human clinical trials to test a number of therapeutic strategies are underway or imminent, facilitated in part by the recent development of biomarkers that might be used as surrogate endpoints in such trials. However, although much progress in developing HD biomarkers has been made, ongoing work seeks to improve the sensitivity and reliability of current measures, and to demonstrate that they correspond to clear meaningful benefit to patients. Of particular importance is the identification of state biomarkers that can be used in pre-manifest HD gene carriers to test therapies hoped to delay symptom onset in these individuals. Functional, neuroimaging and biochemical biomarkers continue to be investigated for use in the development of disease-modifying treatments of HD.