Assessment of Perivascular Space Morphometry Across the White Matter in Huntington's Disease Using MRI

Background

Perivascular spaces (PVS) are fluid-filled cavities surrounding small cerebral blood vessels. There are limited reports of enlarged PVS across the grey matter in manifest Huntington's disease (HD). Little is known about how PVS morphometry in the white matter may contribute to HD. Enlarged PVS have the potential to both contribute to HD pathology and affect the distribution and success of intraparenchymal and intrathecally administered huntingtin-lowering therapies.

Objective

To investigate PVS morphometry in the global white matter across the spectrum of HD. Relationships between PVS morphometry and disease burden and severity measures were examined.

Methods

White matter PVS were segmented on 3T T2 W MRI brain scans of 33 healthy controls, 30 premanifest HD (pre-HD), and 32 early manifest HD (early-HD) participants from the Vancouver site of the TRACK-HD study. PVS count and total PVS volume were measured.

Results

PVS total count slightly increased in pre-HD (p = 0.004), and early-HD groups (p = 0.005), compared to healthy controls. PVS volume, as a percentage of white matter volume, increased subtly in pre-HD compared to healthy controls (p = 0.044), but not in early-HD. No associations between PVS measures and HD disease burden or severity were found.

Conclusions

This study reveals relatively preserved PVS morphometry across the global white matter of pre-HD and early-HD. Subtle morphometric abnormalities are implied but require confirmation in a larger cohort. However, in conjunction with previous publications, further investigation of PVS in HD and its potential impact on future treatments, with a focus on subcortical grey matter, is warranted.

Freesurfer Software Update Significantly Impacts Striatal Volumes in the Huntington's Disease Young Adult Study and Will Influence HD-ISS Staging

Background

The Huntington's Disease Integrated Staging System (HD-ISS) defined disease onset using volumetric cut-offs for caudate and putamen derived from FreeSurfer 6 (FS6). The impact of the latest software update (FS7) on volumes remains unknown. The Huntington's Disease Young Adult Study (HD-YAS) is appropriately positioned to explore differences in FS bias when detecting early atrophy.

Objective

Explore the relationships and differences between raw caudate and putamen volumes, calculated total intracranial volumes (cTICV), and adjusted caudate and putamen volumes, derived from FS6 and FS7, in HD-YAS.

Methods

Images from 123 participants were segmented and quality controlled. Relationships and differences between volumes were explored using intraclass correlation (ICC) and Bland-Altman analysis.

Results

Across the whole cohort, ICC for raw caudate and putamen was 0.99, cTICV 0.93, adjusted caudate 0.87, and adjusted putamen 0.86 (all p < 0.0005). Compared to FS6, FS7 calculated: i) larger raw caudate (+0.8%, p < 0.00005) and putamen (+1.9%, p < 0.00005), with greater difference for larger volumes; and ii) smaller cTICV (-5.1%, p < 0.00005), with greater difference for smaller volumes. The systematic and proportional difference in cTICV was greater than raw volumes. When raw volumes were adjusted for cTICV, these effects compounded (adjusted caudate +7.0%, p < 0.00005; adjusted putamen +8.2%, p < 0.00005), with greater difference for larger volumes.

Conclusions

As new software is released, it is critical that biases are explored since differences have the potential to significantly alter the findings of HD trials. Until conversion factors are defined, the HD-ISS must be applied using FS6. This should be incorporated into the HD-ISS online calculator.

Genetic topography and cortical cell loss in Huntington's disease link development and neurodegeneration

Cortical cell loss is a core feature of Huntington's disease (HD), beginning many years before clinical motor diagnosis, during the premanifest stage. However, it is unclear how genetic topography relates to cortical cell loss. Here, we explore the biological processes and cell types underlying this relationship and validate these using cell-specific post-mortem data. Eighty premanifest participants on average 15 years from disease onset and 71 controls were included. Using volumetric and diffusion MRI we extracted HD-specific whole brain maps where lower grey matter volume and higher grey matter mean diffusivity, relative to controls, were used as proxies of cortical cell loss. These maps were combined with gene expression data from the Allen Human Brain Atlas (AHBA) to investigate the biological processes relating genetic topography and cortical cell loss. Cortical cell loss was positively correlated with the expression of developmental genes (i.e. higher expression correlated with greater atrophy and increased diffusivity) and negatively correlated with the expression of synaptic and metabolic genes that have been implicated in neurodegeneration. These findings were consistent for diffusion MRI and volumetric HD-specific brain maps. As wild-type huntingtin is known to play a role in neurodevelopment, we explored the association between wild-type huntingtin (HTT) expression and developmental gene expression across the AHBA. Co-expression network analyses in 134 human brains free of neurodegenerative disorders were also performed. HTT expression was correlated with the expression of genes involved in neurodevelopment while co-expression network analyses also revealed that HTT expression was associated with developmental biological processes. Expression weighted cell-type enrichment (EWCE) analyses were used to explore which specific cell types were associated with HD cortical cell loss and these associations were validated using cell specific single nucleus RNAseq (snRNAseq) data from post-mortem HD brains. The developmental transcriptomic profile of cortical cell loss in preHD was enriched in astrocytes and endothelial cells, while the neurodegenerative transcriptomic profile was enriched for neuronal and microglial cells. Astrocyte-specific genes differentially expressed in HD post-mortem brains relative to controls using snRNAseq were enriched in the developmental transcriptomic profile, while neuronal and microglial-specific genes were enriched in the neurodegenerative transcriptomic profile. Our findings suggest that cortical cell loss in preHD may arise from dual pathological processes, emerging as a consequence of neurodevelopmental changes, at the beginning of life, followed by neurodegeneration in adulthood, targeting areas with reduced expression of synaptic and metabolic genes. These events result in age-related cell death across multiple brain cell types.

Longitudinal imaging highlights preferential basal ganglia circuit atrophy in Huntington's disease

Huntington's disease is caused by a CAG repeat expansion in the Huntingtin gene (HTT), coding for polyglutamine in the Huntingtin protein, with longer CAG repeats causing earlier age of onset. The variable 'Age' × ('CAG'-L), where 'Age' is the current age of the individual, 'CAG' is the repeat length and L is a constant (reflecting an approximation of the threshold), termed the 'CAG Age Product' (CAP) enables the consideration of many individuals with different CAG repeat expansions at the same time for analysis of any variable and graphing using the CAG Age Product score as the X axis. Structural MRI studies have showed that progressive striatal atrophy begins many years prior to the onset of diagnosable motor Huntington's disease, confirmed by longitudinal multicentre studies on three continents, including PREDICT-HD, TRACK-HD and IMAGE-HD. However, previous studies have not clarified the relationship between striatal atrophy, atrophy of other basal ganglia structures, and atrophy of other brain regions. The present study has analysed all three longitudinal datasets together using a single image segmentation algorithm and combining data from a large number of subjects across a range of CAG Age Product score. In addition, we have used a strategy of normalizing regional atrophy to atrophy of the whole brain, in order to determine which regions may undergo preferential degeneration. This made possible the detailed characterization of regional brain atrophy in relation to CAG Age Product score. There is dramatic selective atrophy of regions involved in the basal ganglia circuit-caudate, putamen, nucleus accumbens, globus pallidus and substantia nigra. Most other regions of the brain appear to have slower but steady degeneration. These results support (but certainly do not prove) the hypothesis of circuit-based spread of pathology in Huntington's disease, possibly due to spread of mutant Htt protein, though other connection-based mechanisms are possible. Therapeutic targets related to prion-like spread of pathology or other mechanisms may be suggested. In addition, they have implications for current neurosurgical therapeutic approaches, since delivery of therapeutic agents solely to the caudate and putamen may miss other structures affected early, such as nucleus accumbens and output nuclei of the striatum, the substantia nigra and the globus pallidus.

The temporal event-based model: Learning event timelines in progressive diseases

Timelines of events, such as symptom appearance or a change in biomarker value, provide powerful signatures that characterise progressive diseases. Understanding and predicting the timing of events is important for clinical trials targeting individuals early in the disease course when putative treatments are likely to have the strongest effect. However, previous models of disease progression cannot estimate the time between events and provide only an ordering in which they change. Here, we introduce the temporal event-based model (TEBM), a new probabilistic model for inferring timelines of biomarker events from sparse and irregularly sampled datasets. We demonstrate the power of the TEBM in two neurodegenerative conditions: Alzheimer's disease (AD) and Huntington's disease (HD). In both diseases, the TEBM not only recapitulates current understanding of event orderings but also provides unique new ranges of timescales between consecutive events. We reproduce and validate these findings using external datasets in both diseases. We also demonstrate that the TEBM improves over current models; provides unique stratification capabilities; and enriches simulated clinical trials to achieve a power of 80 % with less than half the cohort size compared with random selection. The application of the TEBM naturally extends to a wide range of progressive conditions.

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.

Neurofilament light-associated connectivity in young-adult Huntington's disease is related to neuronal genes

Upregulation of functional network connectivity in the presence of structural degeneration is seen in the premanifest stages of Huntington's disease (preHD) 10-15 years from clinical diagnosis. However, whether widespread network connectivity changes are seen in gene carriers much further from onset has yet to be explored. We characterized functional network connectivity throughout the brain and related it to a measure of disease pathology burden (CSF neurofilament light, NfL) and measures of structural connectivity in asymptomatic gene carriers, on average 24 years from onset. We related these measurements to estimates of cortical and subcortical gene expression. We found no overall differences in functional (or structural) connectivity anywhere in the brain comparing control and preHD participants. However, increased functional connectivity, particularly between posterior cortical areas, correlated with increasing CSF NfL level in preHD participants. Using the Allen Human Brain Atlas and expression-weighted cell-type enrichment analysis, we demonstrated that this functional connectivity upregulation occurred in cortical regions associated with regional expression of genes specific to neuronal cells. This relationship was validated using single-nucleus RNAseq data from post-mortem Huntington's disease and control brains showing enrichment of neuronal-specific genes that are differentially expressed in Huntington's disease. Functional brain networks in asymptomatic preHD gene carriers very far from disease onset show evidence of upregulated connectivity correlating with increased disease burden. These changes occur among brain areas that show regional expression of genes specific to neuronal GABAergic and glutamatergic cells.

Forecasting individual progression trajectories in Huntington disease enables more powered clinical trials

Variability in neurodegenerative disease progression poses great challenges for the evaluation of potential treatments. Identifying the persons who will experience significant progression in the short term is key for the implementation of trials with smaller sample sizes. We apply here disease course mapping to forecast biomarker progression for individual carriers of the pathological CAG repeat expansions responsible for Huntington disease. We used data from two longitudinal studies (TRACK-HD and TRACK-ON) to synchronize temporal progression of 15 clinical and imaging biomarkers from 290 participants with Huntington disease. We used then the resulting HD COURSE MAP to forecast clinical endpoints from the baseline data of 11,510 participants from ENROLL-HD, an external validation cohort. We used such forecasts to select participants at risk for progression and compute the power of trials for such an enriched population. HD COURSE MAP forecasts biomarkers 5 years after the baseline measures with a maximum mean absolute error of 10 points for the total motor score and 2.15 for the total functional capacity. This allowed reducing sample sizes in trial up to 50% including participants with a higher risk for progression ensuring a more homogeneous group of participants.

Intellectual enrichment and genetic modifiers of cognition and brain volume in Huntington's disease

An important step towards the development of treatments for cognitive impairment in ageing and neurodegenerative diseases is to identify genetic and environmental modifiers of cognitive function and understand the mechanism by which they exert an effect. In Huntington's disease, the most common autosomal dominant dementia, a small number of studies have identified intellectual enrichment, i.e. a cognitively stimulating lifestyle and genetic polymorphisms as potential modifiers of cognitive function. The aim of our study was to further investigate the relationship and interaction between genetic factors and intellectual enrichment on cognitive function and brain atrophy in Huntington's disease. For this purpose, we analysed data from Track-HD, a multi-centre longitudinal study in Huntington's disease gene carriers and focused on the role of intellectual enrichment (estimated at baseline) and the genes FAN1, MSH3, BDNF, COMT and MAPT in predicting cognitive decline and brain atrophy. We found that carrying the 3a allele in the MSH3 gene had a positive effect on global cognitive function and brain atrophy in multiple cortical regions, such that 3a allele carriers had a slower rate of cognitive decline and atrophy compared with non-carriers, in agreement with its role in somatic instability. No other genetic predictor had a significant effect on cognitive function and the effect of MSH3 was independent of intellectual enrichment. Intellectual enrichment also had a positive effect on cognitive function; participants with higher intellectual enrichment, i.e. those who were better educated, had higher verbal intelligence and performed an occupation that was intellectually engaging, had better cognitive function overall, in agreement with previous studies in Huntington's disease and other dementias. We also found that intellectual enrichment interacted with the BDNF gene, such that the positive effect of intellectual enrichment was greater in Met66 allele carriers than non-carriers. A similar relationship was also identified for changes in whole brain and caudate volume; the positive effect of intellectual enrichment was greater for Met66 allele carriers, rather than for non-carriers. In summary, our study provides additional evidence for the beneficial role of intellectual enrichment and carrying the 3a allele in MSH3 in cognitive function in Huntington's disease and their effect on brain structure.

Longitudinal evaluation of proton magnetic resonance spectroscopy metabolites as biomarkers in Huntington’s disease

Proton magnetic resonance spectroscopy is a non-invasive method of exploring cerebral metabolism. In Huntington’s disease, altered proton magnetic resonance spectroscopy-determined concentrations of several metabolites have been described; however, findings are often discrepant and longitudinal studies are lacking. Proton magnetic resonance spectroscopy metabolites may represent a source of biomarkers, thus their relationship with established markers of disease progression require further exploration to assess prognostic value and elucidate pathways associated with neurodegeneration. In a prospective single-site controlled cohort study with standardized collection of CSF, blood, phenotypic and volumetric imaging data, we used 3 T proton magnetic resonance spectroscopy in conjunction with the linear combination of model spectra method to quantify seven metabolites (total n-acetylaspartate, total creatine, total choline, myo-inositol, GABA, glutamate and glutathione) in the putamen of 59 participants at baseline (15 healthy controls, 15 premanifest and 29 manifest Huntington’s disease gene expansion carriers) and 48 participants at 2-year follow-up (12 healthy controls, 13 premanifest and 23 manifest Huntington’s disease gene expansion carriers). Intergroup differences in concentration and associations with CSF and plasma biomarkers; including neurofilament light chain and mutant Huntingtin, volumetric imaging markers; namely whole brain, caudate, grey matter and white matter volume, measures of disease progression and cognitive decline, were assessed cross-sectionally using generalized linear models and partial correlation. We report no significant groupwise differences in metabolite concentration at baseline but found total creatine and total n-acetylaspartate to be significantly reduced in manifest compared with premanifest participants at follow-up. Additionally, total creatine and myo-inositol displayed significant associations with reduced caudate volume across both time points in gene expansion carriers. Although relationships were observed between proton magnetic resonance spectroscopy metabolites and biofluid measures, these were not consistent across time points. To further assess prognostic value, we examined whether baseline proton magnetic resonance spectroscopy values, or rate of change, predicted subsequent change in established measures of disease progression. Several associations were found but were inconsistent across known indicators of disease progression. Finally, longitudinal mixed-effects models revealed glutamine + glutamate to display a slow linear decrease over time in gene expansion carriers. Altogether, our findings show some evidence of reduced total n-acetylaspartate and total creatine as the disease progresses and cross-sectional associations between select metabolites, namely total creatine and myo-inositol, and markers of disease progression, potentially highlighting the proposed roles of neuroinflammation and metabolic dysfunction in disease pathogenesis. However, the absence of consistent group differences, inconsistency between baseline and follow-up, and lack of clear longitudinal change suggests that proton magnetic resonance spectroscopy metabolites have limited potential as Huntington’s disease biomarkers.

Potential disease-modifying therapies for Huntington's disease: lessons learned and future opportunities

Huntington's disease is the most frequent autosomal dominant neurodegenerative disorder; however, no disease-modifying interventions are available for patients with this disease. The molecular pathogenesis of Huntington's disease is complex, with toxicity that arises from full-length expanded huntingtin and N-terminal fragments of huntingtin, which are both prone to misfolding due to proteolysis; aberrant intron-1 splicing of the HTT gene; and somatic expansion of the CAG repeat in the HTT gene. Potential interventions for Huntington's disease include therapies targeting huntingtin DNA and RNA, clearance of huntingtin protein, DNA repair pathways, and other treatment strategies targeting inflammation and cell replacement. The early termination of trials of the antisense oligonucleotide tominersen suggest that it is time to reflect on lessons learned, where the field stands now, and the challenges and opportunities for the future.

Biological and clinical manifestations of Huntington’s disease in gene carriers very far from predicted onset

Introduction

Crucial to the future success of treatments in Huntington’s disease is identifying a timepoint where there is a measurable biomarker of early neurodegeneration without detectable changes in clinical function. By performing deep phenotyping in premanifest gene carriers (preHD) further from predicted onset than previously studied, we aimed to identify this timepoint and the best measures for efficacy endpoints in future therapeutic trials.

Methods

We recruited 64 young adult preHD, approximately 24 years from predicted clinical onset, and 67 matched controls. All participants underwent detailed cognitive and neuropsychiatric assessments, multi-modal imaging and collection of blood and cerebrospinal fluid (CSF).

Results

We found no significant evidence of cognitive or psychiatric impairment in preHD (minimum q>0.22). The PreHD cohort had smaller putamen volumes (q=0.03), but this was not related to predicted years to onset. There were no group differences in other brain imaging measures (q>0.16). CSF and plasma neurofilament light (NfL) (q<0.0001 and q=0.01) and YKL-40 (q=0.03) were elevated in preHD.

Conclusion

With normal brain function but with sensitive measures of neurodegeneration starting to rise, this stage of preHD may represent an optimal time to initiate future disease-modifying prevention treatments. CSF NfL appears more sensitive at this time than plasma NfL to monitor treatment response.

p.d.zeun@gmail.com

Timing of selective basal ganglia white matter loss in premanifest Huntington's disease

OBJECTIVES

To investigate the timeframe prior to symptom onset when cortico-basal ganglia white matter (white matter) loss begins in premanifest Huntington's disease (preHD), and which striatal and thalamic sub-region white matter tracts are most vulnerable.

METHODS

We performed fixel-based analysis, which allows resolution of crossing white matter fibres at the voxel level, on diffusion tractography derived white matter tracts of striatal and thalamic sub-regions in two independent cohorts; TrackON-HD, which included 72 preHD (approx. 11 years before disease onset) and 85 controls imaged at three time points over two years; and the HD young adult study (HD-YAS), which included 54 preHD (approx. 25 years before disease onset) and 53 controls, imaged at one time point. Group differences in fibre density and cross section (FDC) were investigated.

RESULTS

We found no significant group differences in cortico-basal ganglia sub-region FDC in preHD gene carriers 25 years before onset. In gene carriers 11 years before onset, there were reductions in striatal (limbic and caudal motor) and thalamic (premotor, motor and sensory) FDC at baseline, with no significant change over 2 years. Caudal motor-striatal, pre-motor-thalamic, and primary motor-thalamic FDC at baseline, showed significant correlations with the Unified Huntington's disease rating scale (UHDRS) total motor score (TMS). Limbic cortico-striatal FDC and apathy were also significantly correlated.

CONCLUSIONS

Our findings suggest that limbic and motor white matter tracts to the striatum and thalamus are most susceptible to early degeneration in HD but that approximately 25 years from onset, these tracts appear preserved. These findings may have importance in determining the optimum time to initiate future disease modifying therapies in HD.

Recommendations to Optimize the Use of Volumetric MRI in Huntington's Disease Clinical Trials

Volumetric magnetic resonance imaging (vMRI) has been widely studied in Huntington's disease (HD) and is commonly used to assess treatment effects on brain atrophy in interventional trials. Global and regional trajectories of brain atrophy in HD, with early involvement of striatal regions, are becoming increasingly understood. However, there remains heterogeneity in the methods used and a lack of widely-accessible multisite, longitudinal, normative datasets in HD. Consensus for standardized practices for data acquisition, analysis, sharing, and reporting will strengthen the interpretation of vMRI results and facilitate their adoption as part of a pathobiological disease staging system. The Huntington's Disease Regulatory Science Consortium (HD-RSC) currently comprises 37 member organizations and is dedicated to building a regulatory science strategy to expedite the approval of HD therapeutics. Here, we propose four recommendations to address vMRI standardization in HD research: (1) a checklist of standardized practices for the use of vMRI in clinical research and for reporting results; (2) targeted research projects to evaluate advanced vMRI methodologies in HD; (3) the definition of standard MRI-based anatomical boundaries for key brain structures in HD, plus the creation of a standard reference dataset to benchmark vMRI data analysis methods; and (4) broad access to raw images and derived data from both observational studies and interventional trials, coded to protect participant identity. In concert, these recommendations will enable a better understanding of disease progression and increase confidence in the use of vMRI for drug development.

Volumetric MRI-Based Biomarkers in Huntington's Disease: An Evidentiary Review

Huntington's disease (HD) is an autosomal-dominant inherited neurodegenerative disorder that is caused by expansion of a CAG-repeat tract in the huntingtin gene and characterized by motor impairment, cognitive decline, and neuropsychiatric disturbances. Neuropathological studies show that disease progression follows a characteristic pattern of brain atrophy, beginning in the basal ganglia structures. The HD Regulatory Science Consortium (HD-RSC) brings together diverse stakeholders in the HD community—biopharmaceutical industry, academia, nonprofit, and patient advocacy organizations—to define and address regulatory needs to accelerate HD therapeutic development. Here, the Biomarker Working Group of the HD-RSC summarizes the cross-sectional evidence indicating that regional brain volumes, as measured by volumetric magnetic resonance imaging, are reduced in HD and are correlated with disease characteristics. We also evaluate the relationship between imaging measures and clinical change, their longitudinal change characteristics, and within-individual longitudinal associations of imaging with disease progression. This analysis will be valuable in assessing pharmacodynamics in clinical trials and supporting clinical outcome assessments to evaluate treatment effects on neurodegeneration.

Revealing the Timeline of Structural MRI Changes in Premanifest to Manifest Huntington Disease

BACKGROUND AND OBJECTIVES

Longitudinal measurements of brain atrophy using structural MRI (sMRI) can provide powerful markers for tracking disease progression in neurodegenerative diseases. In this study, we use a disease progression model to learn individual-level disease times and hence reveal a new timeline of sMRI changes in Huntington disease (HD).

METHODS

We use data from the 2 largest cohort imaging studies in HD-284 participants from TRACK-HD (100 control, 104 premanifest, and 80 manifest) and 159 participants from PREDICT-HD (36 control and 128 premanifest)-to train and test the model. We longitudinally register T1-weighted sMRI scans from 3 consecutive time points to reduce intraindividual variability and calculate regional brain volumes using an automated segmentation tool with rigorous manual quality control.

RESULTS

Our model reveals, for the first time, the relative magnitude and timescale of subcortical and cortical atrophy changes in HD. We find that the largest (∼20% average change in magnitude) and earliest (∼2 years before average abnormality) changes occur in the subcortex (pallidum, putamen, and caudate), followed by a cascade of changes across other subcortical and cortical regions over a period of ∼11 years. We also show that sMRI, when combined with our disease progression model, provides improved prediction of onset over the current best method (root mean square error = 4.5 years and maximum error = 7.9 years vs root mean square error = 6.6 years and maximum error = 18.2 years).

DISCUSSION

Our findings support the use of disease progression modeling to reveal new information from sMRI, which can potentially inform imaging marker selection for clinical trials.

Aberrant Striatal Value Representation in Huntington's Disease Gene Carriers 25 Years Before Onset

BACKGROUND

In this study, we asked whether differences in striatal activity during a reinforcement learning (RL) task with gain and loss domains could be one of the earliest functional imaging features associated with carrying the Huntington's disease (HD) gene. Based on previous work, we hypothesized that HD gene carriers would show either neural or behavioral asymmetry between gain and loss learning.

METHODS

We recruited 35 HD gene carriers, expected to demonstrate onset of motor symptoms in an average of 26 years, and 35 well-matched gene-negative control subjects. Participants were placed in a functional magnetic resonance imaging scanner, where they completed an RL task in which they were required to learn to choose between abstract stimuli with the aim of gaining rewards and avoiding losses. Task behavior was modeled using an RL model, and variables from this model were used to probe functional magnetic resonance imaging data.

RESULTS

In comparison with well-matched control subjects, gene carriers more than 25 years from motor onset showed exaggerated striatal responses to gain-predicting stimuli compared with loss-predicting stimuli (p = .002) in our RL task. Using computational analysis, we also found group differences in striatal representation of stimulus value (p = .0004). We found no group differences in behavior, cognitive scores, or caudate volumes.

CONCLUSIONS

Behaviorally, gene carriers 9 years from predicted onset have been shown to learn better from gains than from losses. Our data suggest that a window exists in which HD-related functional neural changes are detectable long before associated behavioral change and 25 years before predicted motor onset. These represent the earliest functional imaging differences between HD gene carriers and control subjects.

A Multi-Study Model-Based Evaluation of the Sequence of Imaging and Clinical Biomarker Changes in Huntington's Disease

Understanding the order and progression of change in biomarkers of neurodegeneration is essential to detect the effects of pharmacological interventions on these biomarkers. In Huntington’s disease (HD), motor, cognitive and MRI biomarkers are currently used in clinical trials of drug efficacy. Here for the first time we use directly compare data from three large observational studies of HD (total N = 532) using a probabilistic event-based model (EBM) to characterise the order in which motor, cognitive and MRI biomarkers become abnormal. We also investigate the impact of the genetic cause of HD, cytosine-adenine-guanine (CAG) repeat length, on progression through these stages. We find that EBM uncovers a broadly consistent order of events across all three studies; that EBM stage reflects clinical stage; and that EBM stage is related to age and genetic burden. Our findings indicate that measures of subcortical and white matter volume become abnormal prior to clinical and cognitive biomarkers. Importantly, CAG repeat length has a large impact on the timing of onset of each stage and progression through the stages, with a longer repeat length resulting in earlier onset and faster progression. Our results can be used to help design clinical trials of treatments for Huntington’s disease, influencing the choice of biomarkers and the recruitment of participants.

Kynurenine pathway metabolites in cerebrospinal fluid and blood as potential biomarkers in Huntington's disease

Converging lines of evidence from several models, and post-mortem human brain tissue studies, support the involvement of the kynurenine pathway (KP) in Huntington's disease (HD) pathogenesis. Quantifying KP metabolites in HD biofluids is desirable, both to study pathobiology and as a potential source of biomarkers to quantify pathway dysfunction and evaluate the biochemical impact of therapeutic interventions targeting its components. In a prospective single-site controlled cohort study with standardised collection of cerebrospinal fluid (CSF), blood, phenotypic and imaging data, we used high-performance liquid-chromatography to measure the levels of KP metabolites-tryptophan, kynurenine, kynurenic acid, 3-hydroxykynurenine, anthranilic acid and quinolinic acid-in CSF and plasma of 80 participants (20 healthy controls, 20 premanifest HD and 40 manifest HD). We investigated short-term stability, intergroup differences, associations with clinical and imaging measures and derived sample-size calculation for future studies. Overall, KP metabolites in CSF and plasma were stable over 6 weeks, displayed no significant group differences and were not associated with clinical or imaging measures. We conclude that the studied metabolites are readily and reliably quantifiable in both biofluids in controls and HD gene expansion carriers. However, we found little evidence to support a substantial derangement of the KP in HD, at least to the extent that it is reflected by the levels of the metabolites in patient-derived biofluids.

Dynamics of Cortical Degeneration Over a Decade in Huntington's Disease

BACKGROUND

Characterizing changing brain structure in neurodegeneration is fundamental to understanding long-term effects of pathology and ultimately providing therapeutic targets. It is well established that Huntington's disease (HD) gene carriers undergo progressive brain changes during the course of disease, yet the long-term trajectory of cortical atrophy is not well defined. Given that genetic therapies currently tested in HD are primarily expected to target the cortex, understanding atrophy across this region is essential.

METHODS

Capitalizing on a unique longitudinal dataset with a minimum of 3 and maximum of 7 brain scans from 49 HD gene carriers and 49 age-matched control subjects, we implemented a novel dynamical systems approach to infer patterns of regional neurodegeneration over 10 years. We use Bayesian hierarchical modeling to map participant- and group-level trajectories of atrophy spatially and temporally, additionally relating atrophy to the genetic marker of HD (CAG-repeat length) and motor and cognitive symptoms.

RESULTS

We show, for the first time, that neurodegenerative changes exhibit complex temporal dynamics with substantial regional variation around the point of clinical diagnosis. Although widespread group differences were seen across the cortex, the occipital and parietal regions undergo the greatest rate of cortical atrophy. We have established links between atrophy and genetic markers of HD while demonstrating that specific cortical changes predict decline in motor and cognitive performance.

CONCLUSIONS

HD gene carriers display regional variability in the spatial pattern of cortical atrophy, which relates to genetic factors and motor and cognitive symptoms. Our findings indicate a complex pattern of neuronal loss, which enables greater characterization of HD progression.

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.

Brain-derived neurotrophic factor in cerebrospinal fluid and plasma is not a biomarker for Huntington's disease

Brain-derived neurotrophic factor (BDNF) is implicated in the survival of striatal neurons. BDNF function is reduced in Huntington's disease (HD), possibly because mutant huntingtin impairs its cortico-striatal transport, contributing to striatal neurodegeneration. The BDNF trophic pathway is a therapeutic target, and blood BDNF has been suggested as a potential biomarker for HD, but BDNF has not been quantified in cerebrospinal fluid (CSF) in HD. We quantified BDNF in CSF and plasma in the HD-CSF cohort (20 pre-manifest and 40 manifest HD mutation carriers and 20 age and gender-matched controls) using conventional ELISAs and an ultra-sensitive immunoassay. BDNF concentration was below the limit of detection of the conventional ELISAs, raising doubt about previous CSF reports in neurodegeneration. Using the ultra-sensitive method, BDNF concentration was quantifiable in all samples but did not differ between controls and HD mutation carriers in CSF or plasma, was not associated with clinical scores or MRI brain volumetric measures, and had poor ability to discriminate controls from HD mutation carriers, and premanifest from manifest HD. We conclude that BDNF in CSF and plasma is unlikely to be a biomarker of HD progression and urge caution in interpreting studies where conventional ELISA was used to quantify CSF BDNF.

Fronto-striatal circuits for cognitive flexibility in far from onset Huntington's disease: evidence from the Young Adult Study

OBJECTIVES

Cognitive flexibility, which is key for adaptive decision-making, engages prefrontal cortex (PFC)-striatal circuitry and is impaired in both manifest and premanifest Huntington's disease (pre-HD). The aim of this study was to examine cognitive flexibility in a far from onset pre-HD cohort to determine whether an early impairment exists and if so, whether fronto-striatal circuits were associated with this deficit.

METHODS

In the present study, we examined performance of 51 pre-HD participants (mean age=29.22 (SD=5.71) years) from the HD Young Adult Study cohort and 53 controls matched for age, sex and IQ, on the Cambridge Neuropsychological Test Automated Battery (CANTAB) Intra-Extra Dimensional Set-Shift (IED) task. This cohort is unique as it is the furthest from disease onset comprehensively studied to date (mean years=23.89 (SD=5.96) years). The IED task measures visual discrimination learning, cognitive flexibility and specifically attentional set-shifting. We used resting-state functional MRI to examine whether the functional connectivity between specific fronto-striatal circuits was dysfunctional in pre-HD, compared with controls, and whether these circuits were associated with performance on the critical extradimensional shift stage.

RESULTS

Our results demonstrated that the CANTAB IED task detects a mild early impairment in cognitive flexibility in a pre-HD group far from onset. Attentional set-shifting was significantly related to functional connectivity between the ventrolateral PFC and ventral striatum in healthy controls and to functional connectivity between the dorsolateral PFC and caudate in pre-HD participants.

CONCLUSION

We postulate that this incipient impairment of cognitive flexibility may be associated with intrinsically abnormal functional connectivity of fronto-striatal circuitry in pre-HD.

Composite UHDRS Correlates With Progression of Imaging Biomarkers in Huntington's Disease

BACKGROUND

The composite Unified Huntington's Disease Rating Scale (cUHDRS) is a multidimensional measure of progression in Huntington's disease (HD) being used as a primary outcome in clinical trials investigating potentially disease-modifying huntingtin-lowering therapies.

OBJECTIVE

Evaluating volumetric and structural connectivity correlates of the cUHDRS.

METHODS

One hundred and nineteen premanifest and 119 early-HD participants were included. Gray and white matter (WM) volumes were correlated with cUHDRS cross-sectionally and longitudinally using voxel-based morphometry. Correlations between baseline fractional anisotropy (FA); mean, radial, and axial diffusivity; and baseline cUHDRS were examined using tract-based spatial statistics.

RESULTS

Worse performance in the cUHDRS over time correlated with longitudinal volume decreases in the occipito-parietal cortex and centrum semiovale, whereas lower baseline scores correlated with decreased volume in the basal ganglia and surrounding WM. Lower cUHDRS scores were also associated with reduced FA and increased diffusivity at baseline.

CONCLUSION

The cUHDRS correlates with imaging biomarkers and tracks atrophy progression in HD supporting its biological relevance. © 2021 International Parkinson and Movement Disorder Society.

Mutant huntingtin and neurofilament light have distinct longitudinal dynamics in Huntington's disease

The longitudinal dynamics of the most promising biofluid biomarker candidates for Huntington's disease (HD)-mutant huntingtin (mHTT) and neurofilament light (NfL)-are incompletely defined. Characterizing changes in these candidates during disease progression could increase our understanding of disease pathophysiology and help the identification of effective therapies. In an 80-participant cohort over 24 months, mHTT in cerebrospinal fluid (CSF), as well as NfL in CSF and blood, had distinct longitudinal trajectories in HD mutation carriers compared with controls. Baseline analyte values predicted clinical disease status, subsequent clinical progression, and brain atrophy, better than did the rate of change in analytes. Overall, NfL was a stronger monitoring and prognostic biomarker for HD than mHTT. Nonetheless, mHTT has prognostic value and might be a valuable pharmacodynamic marker for huntingtin-lowering trials.

Biological and clinical characteristics of gene carriers far from predicted onset in the Huntington's disease Young Adult Study (HD-YAS): a cross-sectional analysis

BACKGROUND

Disease-modifying treatments are in development for Huntington's disease; crucial to their success is to identify a timepoint in a patient's life when there is a measurable biomarker of early neurodegeneration while clinical function is still intact. We aimed to identify this timepoint in a novel cohort of young adult premanifest Huntington's disease gene carriers (preHD) far from predicted clinical symptom onset.

METHODS

We did the Huntington's disease Young Adult Study (HD-YAS) in the UK. We recruited young adults with preHD and controls matched for age, education, and sex to ensure each group had at least 60 participants with imaging data, accounting for scan fails. Controls either had a family history of Huntington's disease but a negative genetic test, or no known family history of Huntington's disease. All participants underwent detailed neuropsychiatric and cognitive assessments, including tests from the Cambridge Neuropsychological Test Automated Battery and a battery assessing emotion, motivation, impulsivity and social cognition (EMOTICOM). Imaging (done for all participants without contraindications) included volumetric MRI, diffusion imaging, and multiparametric mapping. Biofluid markers of neuronal health were examined using blood and CSF collection. We did a cross-sectional analysis using general least-squares linear models to assess group differences and associations with age and CAG length, relating to predicted years to clinical onset. Results were corrected for multiple comparisons using the false discovery rate (FDR), with FDR <0·05 deemed a significant result.

FINDINGS

Data were obtained between Aug 2, 2017, and April 25, 2019. We recruited 64 young adults with preHD and 67 controls. Mean ages of participants were 29·0 years (SD 5·6) and 29·1 years (5·7) in the preHD and control groups, respectively. We noted no significant evidence of cognitive or psychiatric impairment in preHD participants 23·6 years (SD 5·8) from predicted onset (FDR 0·22-0·87 for cognitive measures, 0·31-0·91 for neuropsychiatric measures). The preHD cohort had slightly smaller putamen volumes (FDR=0·03), but this did not appear to be closely related to predicted years to onset (FDR=0·54). There were no group differences in other brain imaging measures (FDR >0·16). CSF neurofilament light protein (NfL), plasma NfL, and CSF YKL-40 were elevated in this far-from-onset preHD cohort compared with controls (FDR<0·0001, =0·01, and =0·03, respectively). CSF NfL elevations were more likely in individuals closer to expected clinical onset (FDR <0·0001).

INTERPRETATION

We report normal brain function yet a rise in sensitive measures of neurodegeneration in a preHD cohort approximately 24 years from predicted clinical onset. CSF NfL appears to be a more sensitive measure than plasma NfL to monitor disease progression. This preHD cohort is one of the earliest yet studied, and our findings could be used to inform decisions about when to initiate a potential future intervention to delay or prevent further neurodegeneration while function is intact.

FUNDING

Wellcome Trust, CHDI Foundation.

Longitudinal Structural MRI in Neurologically Healthy Adults

BACKGROUND

Structural brain MRI measures are frequently examined in both healthy and clinical groups, so an understanding of how these measures vary over time is desirable.

PURPOSE

To test the stability of structural brain MRI measures over time.

POPULATION

In all, 112 healthy volunteers across four sites.

STUDY TYPE

Retrospective analysis of prospectively acquired data.

FIELD STRENGTH/SEQUENCE

3 T, magnetization prepared - rapid gradient echo, and single-shell diffusion sequence.

ASSESSMENT

Diffusion, cortical thickness, and volume data from the sensorimotor network were assessed for stability over time across 3 years. Two sites used a Siemens MRI scanner, two sites a Philips scanner.

STATISTICAL TESTS

The stability of structural measures across timepoints was assessed using intraclass correlation coefficients (ICC) for absolute agreement, cutoff ≥0.80, indicating high reliability. Mixed-factorial analysis of variance (ANOVA) was used to examine between-site and between-scanner type differences in individuals over time.

RESULTS

All cortical thickness and gray matter volume measures in the sensorimotor network, plus all diffusivity measures (fractional anisotropy plus mean, axial and radial diffusivities) for primary and premotor cortices, primary somatosensory thalamic connections, and the cortico-spinal tract met ICC. The majority of measures differed significantly between scanners, with a trend for sites using Siemens scanners to produce larger values for connectivity, cortical thickness, and volume measures than sites using Philips scanners.

DATA CONCLUSION

Levels of reliability over time for all tested structural MRI measures were generally high, indicating that any differences between measurements over time likely reflect underlying biological differences rather than inherent methodological variability.

LEVEL OF EVIDENCE

4.

TECHNICAL EFFICACY STAGE

1.

Robust Markers and Sample Sizes for Multicenter Trials of Huntington Disease

Objective

The identification of sensitive biomarkers is essential to validate therapeutics for Huntington disease (HD). We directly compare structural imaging markers across the largest collective imaging HD dataset to identify a set of imaging markers robust to multicenter variation and to derive upper estimates on sample sizes for clinical trials in HD.

Methods

We used 1 postprocessing pipeline to retrospectively analyze T1‐weighted magnetic resonance imaging (MRI) scans from 624 participants at 3 time points, from the PREDICT‐HD, TRACK‐HD, and IMAGE‐HD studies. We used mixed effects models to adjust regional brain volumes for covariates, calculate effect sizes, and simulate possible treatment effects in disease‐affected anatomical regions. We used our model to estimate the statistical power of possible treatment effects for anatomical regions and clinical markers.

Results

We identified a set of common anatomical regions that have similarly large standardized effect sizes (>0.5) between healthy control and premanifest HD (PreHD) groups. These included subcortical, white matter, and cortical regions and nonventricular cerebrospinal fluid (CSF). We also observed a consistent spatial distribution of effect size by region across the whole brain. We found that multicenter studies were necessary to capture treatment effect variance; for a 20% treatment effect, power of >80% was achieved for the caudate (n = 661), pallidum (n = 687), and nonventricular CSF (n = 939), and, crucially, these imaging markers provided greater power than standard clinical markers.

Interpretation

Our findings provide the first cross‐study validation of structural imaging markers in HD, supporting the use of these measurements as endpoints for both observational studies and clinical trials. ANN NEUROL 2020;87:751–762

Characterizing White Matter in Huntington's Disease

BACKGROUND

Investigating early white matter (WM) change in Huntington's disease (HD) can improve our understanding of the way in which disease spreads from the striatum.

OBJECTIVES

We provide a detailed characterization of pathology-related WM change in HD. We first examined WM microstructure using diffusion-weighted imaging and then investigated both underlying biological properties of WM and products of WM damage including iron, myelin plus neurofilament light, a biofluid marker of axonal degeneration-in parallel with the mutant huntingtin protein.

METHODS

We examined WM change in HD gene carriers from the HD-CSFcohort, baseline visit. We used standard-diffusion magnetic resonance imaging to measure metrics including fractional anisotropy, a marker of WM integrity, and diffusivity; a novel diffusion model (neurite orientation dispersion and density imaging) to measure axonal density and organization; T1-weighted and T2-weighted structural magnetic resonance imaging images to derive proxy iron content and myelin-contrast measures; and biofluid concentrations of neurofilament light (in cerebrospinal fluid (CSF) and plasma) and mutant huntingtin protein (in CSF).

RESULTS

HD gene carriers displayed reduced fractional anisotropy and increased diffusivity when compared with controls, both of which were also associated with disease progression, CSF, and mutant huntingtin protein levels. HD gene carriers also displayed proxy measures of reduced myelin contrast and iron in the striatum.

CONCLUSION

Collectively, these findings present a more complete characterization of HD-related microstructural brain changes. The correlation between reduced fractional anisotropy, increased axonal orientation, and biofluid markers suggest that axonal breakdown is associated with increased WM degeneration, whereas higher quantitative T2 signal and lower myelin-contrast may indicate a process of demyelination limited to the striatum.

Identifying disease-associated biomarker network features through conditional graphical model

Biomarkers are often organized into networks, in which the strengths of network connections vary across subjects depending on subject-specific covariates (eg, genetic variants). Variation of network connections, as subject-specific feature variables, has been found to predict disease clinical outcome. In this work, we develop a two-stage method to estimate biomarker networks that account for heterogeneity among subjects and evaluate network's association with disease clinical outcome. In the first stage, we propose a conditional Gaussian graphical model with mean and precision matrix depending on covariates to obtain covariate-dependent networks with connection strengths varying across subjects while assuming homogeneous network structure. In the second stage, we evaluate clinical utility of network measures (connection strengths) estimated from the first stage. The second-stage analysis provides the relative predictive power of between-region network measures on clinical impairment in the context of regional biomarkers and existing disease risk factors. We assess the performance of proposed method by extensive simulation studies and application to a Huntington's disease (HD) study to investigate the effect of HD causal gene on the rate of change in motor symptom through affecting brain subcortical and cortical gray matter atrophy connections. We show that cortical network connections and subcortical volumes, but not subcortical connections are identified to be predictive of clinical motor function deterioration. We validate these findings in an independent HD study. Lastly, highly similar patterns seen in the gray matter connections and a previous white matter connectivity study suggest a shared biological mechanism for HD and support the hypothesis that white matter loss is a direct result of neuronal loss as opposed to the loss of myelin or dysmyelination.

Multimodal characterization of the visual network in Huntington's disease gene carriers

OBJECTIVE

A sensorimotor network structural phenotype predicted motor task performance in a previous study in Huntington's disease (HD) gene carriers. We investigated in the visual network whether structure - function - behaviour relationship patterns, and the effects of the HD mutation, extended beyond the sensorimotor network.

METHODS

We used multimodal visual network MRI structural measures (cortical thickness and white matter connectivity), plus visual evoked potentials and task performance (Map Search; Symbol Digit Modalities Test) in healthy controls and HD gene carriers.

RESULTS

Using principal component (PC) analysis, we identified a structure - function relationship common to both groups. PC scores differed between groups indicating white matter disorganization (higher RD, lower FA) and slower, and more disperse, VEP signal transmission (higher VEP P100 latency and lower VEP P100 amplitude) in HD than controls while task performance was similar.

CONCLUSIONS

HD may be associated with reduced white matter organization and efficient visual network function but normal task performance.

SIGNIFICANCE

These findings indicate that structure - function relationships in the visual network, and the effects of the HD mutation, share some commonalities with those in the sensorimotor network. However, implications for task performance differ between the two networks suggesting the influence of network specific factors.

Association of CAG Repeats With Long-term Progression in Huntington Disease

IMPORTANCE

In Huntington disease (HD), mutation severity is defined by the length of the CAG trinucleotide sequence, a well-known predictor of clinical onset age. The association with disease trajectory is less well characterized. Quantifiable summary measures of trajectory applicable over decades of early disease progression are lacking. An accurate model of the age-CAG association with early progression is critical to clinical trial design, informing both sample size and intervention timing.

OBJECTIVE

To succinctly capture the decades-long early progression of HD and its dependence on CAG repeat length.

DESIGN, SETTING, AND PARTICIPANTS

Prospective study at 4 academic HD treatment and research centers. Participants were the combined sample from the TRACK-HD and Track-On HD studies consisting of 290 gene carriers (presymptomatic to stage II), recruited from research registries at participating centers, and 153 nonbiologically related controls, generally spouses or friends. Recruitment was targeted to match a balanced, prespecified spectrum of age, CAG repeat length, and diagnostic status. In the TRACK-HD and Track-On HD studies, 13 and 5 potential participants, respectively, failed study screening. Follow-up ranged from 0 to 6 years. The study dates were January 2008 to November 2014. These analyses were performed between December 2015 and January 2019.

MAIN OUTCOMES AND MEASURES

The outcome measures were principal component summary scores of motor-cognitive function and of brain volumes. The main outcome was the association of these scores with age and CAG repeat length.

RESULTS

We analyzed 2065 visits from 443 participants (247 female [55.8%]; mean [SD] age, 44.4 [10.3] years). Motor-cognitive measures were highly correlated and had similar CAG repeat length-dependent associations with age. A composite summary score accounted for 67.6% of their combined variance. This score was well approximated by a score combining 3 items (total motor score, Symbol Digit Modalities Test, and Stroop word reading) from the Unified Huntington's Disease Rating Scale. For either score, initial progression age and then acceleration rate were highly CAG repeat length dependent. The acceleration continues through at least stage II disease. In contrast, 3 distinct patterns emerged among brain measures (basal ganglia, gray matter, and a combination of whole-brain, ventricular, and white matter volumes). The basal ganglia pattern showed considerable change in even the youngest participants but demonstrated minimal acceleration of loss with aging. Each clinical and brain summary score was strongly associated with the onset and rate of decline in total functional capacity.

CONCLUSIONS AND RELEVANCE

Results of this study suggest that succinct summary measures of function and brain loss characterize HD progression across a wide disease span. CAG repeat length strongly predicts their decline rate. This work aids our understanding of the age and CAG repeat length-dependent association between changes in the brain and clinical manifestations of HD.

Evaluation of mutant huntingtin and neurofilament proteins as potential markers in Huntington's disease

Huntington's disease (HD) is a genetic progressive neurodegenerative disorder, caused by a mutation in the HTT gene, for which there is currently no cure. The identification of sensitive indicators of disease progression and therapeutic outcome could help the development of effective strategies for treating HD. We assessed mutant huntingtin (mHTT) and neurofilament light (NfL) protein concentrations in cerebrospinal fluid (CSF) and blood in parallel with clinical evaluation and magnetic resonance imaging in premanifest and manifest HD mutation carriers. Among HD mutation carriers, NfL concentrations in plasma and CSF correlated with all nonbiofluid measures more closely than did CSF mHTT concentration. Longitudinal analysis over 4 to 8 weeks showed that CSF mHTT, CSF NfL, and plasma NfL concentrations were highly stable within individuals. In our cohort, concentration of CSF mHTT accurately distinguished between controls and HD mutation carriers, whereas NfL concentration, in both CSF and plasma, was able to segregate premanifest from manifest HD. In silico modeling indicated that mHTT and NfL concentrations in biofluids might be among the earliest detectable alterations in HD, and sample size prediction suggested that low participant numbers would be needed to incorporate these measures into clinical trials. These findings provide evidence that biofluid concentrations of mHTT and NfL have potential for early and sensitive detection of alterations in HD and could be integrated into both clinical trials and the clinic.

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.

Cerebrospinal fluid flow dynamics in Huntington's disease evaluated by phase contrast MRI

Multiple targeted therapeutics for Huntington's disease are now in clinical trials, including intrathecally delivered compounds. Previous research suggests that CSF dynamics may be altered in Huntington's disease, which could be of paramount relevance to intrathecal drug delivery to the brain. To test this hypothesis, we conducted a prospective cross-sectional study comparing people with early stage Huntington's disease with age- and gender-matched healthy controls. CSF peak velocity, mean velocity and mean flow at the level of the cerebral aqueduct, and sub-arachnoid space in the upper and lower spine, were quantified using phase contrast MRI. We calculated Spearman's rank correlations, and tested inter-group differences with Wilcoxon rank-sum test. Ten people with early Huntington's disease, and 10 controls were included. None of the quantified measures was associated with potential modifiers of CSF dynamics (demographics, osmolality, and brain volumes), or by known modifiers of Huntington's disease (age and HTTCAG repeat length); and no significant differences were found between the two studied groups. While external validation is required, the attained results are sufficient to conclude tentatively that a clinically relevant alteration of CSF dynamics - that is, one that would justify dose-adjustments of intrathecal drugs - is unlikely to exist in Huntington's disease.

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Within neuroimaging research, a number of recent studies have discussed the impact of between-study differences in volumetric findings that are thought to result from the use of different segmentation tools to generate brain volumes. Here, processing pipelines for seven automated tools that can be used to segment grey matter within the brain are presented. The protocol provides an initial step for researchers aiming to find the most accurate method for generating grey matter volumes from T1-weighted MRI scans. Steps to undertake detailed visual quality control are also included in the manuscript. This protocol covers a range of potential segmentation tools and encourages users to compare the performance of these tools within a subset of their data before selecting one to apply to a full cohort. Furthermore, the protocol may be further generalized to the segmentation of other brain regions.

Altered Intracortical T1-Weighted/T2-Weighted Ratio Signal in Huntington's Disease

Huntington's disease (HD) is a genetic neurodegenerative disorder that is characterized by neuronal cell death. Although medium spiny neurons in the striatum are predominantly affected, other brain regions including the cerebral cortex also degenerate. Previous structural imaging studies have reported decreases in cortical thickness in HD. Here we aimed to further investigate changes in cortical tissue composition in vivo in HD using standard clinical T1-weighted (T1W) and T2-weighted (T2W) magnetic resonance images (MRIs). 326 subjects from the TRACK-HD dataset representing healthy controls and four stages of HD progression were analyzed. The intracortical T1W/T2W intensity was sampled in the middle depth of the cortex over 82 regions across the cortex. While these previously collected images were not optimized for intracortical analysis, we found a significant increase in T1W/T2W intensity (p < 0.05 Bonferroni-Holm corrected) beginning with HD diagnosis. Increases in ratio intensity were found in the insula, which then spread to ventrolateral frontal cortex, superior temporal gyrus, medial temporal gyral pole, and cuneus with progression into the most advanced HD group studied. Mirroring past histological reports, this increase in the ratio image intensity may reflect disease-related increases in myelin and/or iron in the cortex. These findings suggest that future imaging studies are warranted with imaging optimized to more sensitively and specifically assess which features of cortical tissue composition are abnormal in HD to better characterize disease progression.

Learning Subject-Specific Directed Acyclic Graphs With Mixed Effects Structural Equation Models From Observational Data

The identification of causal relationships between random variables from large-scale observational data using directed acyclic graphs (DAG) is highly challenging. We propose a new mixed-effects structural equation model (mSEM) framework to estimate subject-specific DAGs, where we represent joint distribution of random variables in the DAG as a set of structural causal equations with mixed effects. The directed edges between nodes depend on observed exogenous covariates on each of the individual and unobserved latent variables. The strength of the connection is decomposed into a fixed-effect term representing the average causal effect given the covariates and a random effect term representing the latent causal effect due to unobserved pathways. The advantage of such decomposition is to capture essential asymmetric structural information and heterogeneity between DAGs in order to allow for the identification of causal structure with observational data. In addition, by pooling information across subject-specific DAGs, we can identify causal structure with a high probability and estimate subject-specific networks with a high precision. We propose a penalized likelihood-based approach to handle multi-dimensionality of the DAG model. We propose a fast, iterative computational algorithm, DAG-MM, to estimate parameters in mSEM and achieve desirable sparsity by hard-thresholding the edges. We theoretically prove the identifiability of mSEM. Using simulations and an application to protein signaling data, we show substantially improved performances when compared to existing methods and consistent results with a network estimated from interventional data. Lastly, we identify gray matter atrophy networks in regions of brain from patients with Huntington's disease and corroborate our findings using white matter connectivity data collected from an independent study.

In vivo characterization of white matter pathology in premanifest huntington's disease

OBJECTIVE

Huntington's disease (HD) is a monogenic, fully penetrant neurodegenerative disorder, providing an ideal model for understanding brain changes occurring in the years prior to disease onset. Diffusion tensor imaging (DTI) studies show widespread white matter disorganization in the early premanifest stages (pre-HD). However, although DTI has proved informative, it provides only limited information about underlying changes in tissue properties. Neurite orientation dispersion and density imaging (NODDI) is a novel magnetic resonance imaging (MRI) technique for characterizing axonal pathology more specifically, providing metrics that separately quantify axonal density and axonal organization. Here, we provide the first in vivo characterization of white matter pathology in pre-HD using NODDI.

METHODS

Diffusion-weighted MRI data that support DTI and NODDI were acquired from 38 pre-HD and 45 control participants. Using whole-brain and region-of-interest analyses, NODDI metrics were compared between groups and correlated with clinical scores of disease progression. Whole-brain changes in DTI metrics were also examined.

RESULTS

The pre-HD group displayed widespread reductions in axonal density compared with control participants; this correlated with measures of clinical disease progression in the body and genu of the corpus callosum. There was also evidence in the pre-HD group of increased coherence of axonal packing in the white matter surrounding the basal ganglia.

INTERPRETATION

Our findings suggest that reduced axonal density is one of the major factors underlying white matter pathology in pre-HD, coupled with altered local organization in areas surrounding the basal ganglia. NODDI metrics show promise in providing more specific information about the biological processes underlying HD and neurodegeneration per se. Ann Neurol 2018;84:497-504.

Testing a longitudinal compensation model in premanifest Huntington's disease

The initial stages of neurodegeneration are commonly marked by normal levels of cognitive and motor performance despite the presence of structural brain pathology. Compensation is widely assumed to account for this preserved behaviour, but despite the apparent simplicity of such a concept, it has proven incredibly difficult to demonstrate such a phenomenon and distinguish it from disease-related pathology. Recently, we developed a model of compensation whereby brain activation, behaviour and pathology, components key to understanding compensation, have specific longitudinal trajectories over three phases of progression. Here, we empirically validate our explicit mathematical model by testing for the presence of compensation over time in neurodegeneration. Huntington's disease is an ideal model for examining longitudinal compensation in neurodegeneration as it is both monogenic and fully penetrant, so disease progression and potential compensation can be monitored many years prior to diagnosis. We defined our conditions for compensation as non-linear longitudinal trajectories of brain activity and performance in the presence of linear neuronal degeneration and applied our model of compensation to a large longitudinal cohort of premanifest and early-stage Huntington's disease patients from the multisite Track-On HD study. Focusing on cognitive and motor networks, we integrated progressive volume loss, task and resting state functional MRI and cognitive and motor behaviour across three sequential phases of neurodegenerative disease progression, adjusted for genetic disease load. Multivariate linear mixed models were fitted and trajectories for each variable tested. Our conceptualization of compensation was partially realized across certain motor and cognitive networks at differing levels. We found several significant network trends that were more complex than that hypothesized in our model. These trends suggest changes to our theoretical model where the network effects are delayed relative to performance effects. There was evidence of compensation primarily in the prefrontal component of the cognitive network, with increased effective connectivity between the left and right dorsolateral prefrontal cortex. Having developed an operational model for the explicit testing of longitudinal compensation in neurodegeneration, it appears that general patterns of our framework are consistent with the empirical data. With the proposed modifications, our operational model of compensation can be used to test for both cross-sectional and longitudinal compensation in neurodegenerative disease with similar patterns to Huntington's disease.

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

Huntington's 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.

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.

Apathy and atrophy of subcortical brain structures in Huntington's disease: A two-year follow-up study

Background

Huntington's disease (HD) is characterized by motor and behavioral symptoms, and cognitive decline. HD gene carriers and their caregivers report the behavioral and cognitive symptoms as the most burdensome. Apathy is the most common behavioral symptom of HD and is related to clinical measures of disease progression, like functional capacity. However, it is unknown whether apathy is directly related to the neurodegenerative processes in HD.

Objective

The aim is to investigate whether an association between atrophy of subcortical structures and apathy is present in HD, at baseline and after 2 years follow-up.

Method

Volumes of 7 subcortical structures were measured using structural T1 MRI in 171 HD gene carriers of the TRACK-HD study and apathy was assessed with the Problem Behaviors Assessment-Short, at baseline and follow-up visit. At baseline, logistic regression was used to evaluate whether volumes of subcortical brain structures were associated with the presence of apathy. Linear regression was used to assess whether subcortical atrophy was associated with the degree of apathy at baseline and with an increase in severity of apathy over time.

Results

At baseline, smaller volume of the thalamus showed a higher probability of the presence of apathy in HD gene carriers, but none of the subcortical structures was associated with the degree of apathy. Over time, no association between atrophy of any subcortical structures and change in degree of apathy was found.

Conclusion

The presence of apathy is associated with atrophy of the thalamus in HD, suggesting that apathy has an underlying neural cause and might explain the high incidence of apathy in HD. However, no association was found between atrophy of these subcortical structures and increase in severity of apathy over a 2-year time period.

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker

OBJECTIVE

Huntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real-life clinical diagnosis in HD.

METHOD

A multivariate machine learning approach was applied to resting-state and structural magnetic resonance imaging scans from 19 premanifest HD gene carriers (preHD, 8 of whom developed clinical disease in the 5 years postscanning) and 21 healthy controls. A classification model was developed using cross-group comparisons between preHD and controls, and within the preHD group in relation to "estimated" and "actual" proximity to disease onset. Imaging measures were modeled individually, and combined, and permutation modeling robustly tested classification accuracy.

RESULTS

Classification performance for preHDs versus controls was greatest when all measures were combined. The resulting polymarker predicted converters with high accuracy, including those who were not expected to manifest in that time scale based on the currently adopted statistical models.

INTERPRETATION

We propose that a holistic multivariate machine learning treatment of brain abnormalities in the premanifest phase can be used to accurately identify those patients within 5 years of developing motor features of HD, with implications for prognostication and preclinical trials. Ann Neurol 2018;83:532-543.

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.

Neurofilament light protein in blood predicts regional atrophy in Huntington disease

OBJECTIVE

Neurofilament light (NfL) protein in blood plasma has been proposed as a prognostic biomarker of neurodegeneration in a number of conditions, including Huntington disease (HD). This study investigates the regional distribution of NfL-associated neural pathology in HD gene expansion carriers.

METHODS

We examined associations between NfL measured in plasma and regionally specific atrophy in cross-sectional (n = 198) and longitudinal (n = 177) data in HD gene expansion carriers from the international multisite TRACK-HD study. Using voxel-based morphometry, we measured associations between baseline NfL levels and both baseline gray matter and white matter volume; and longitudinal change in gray matter and white matter over the subsequent 3 years in HD gene expansion carriers.

RESULTS

After controlling for demographics, associations between increased NfL levels and reduced brain volume were seen in cortical and subcortical gray matter and within the white matter. After also controlling for known predictors of disease progression (age and CAG repeat length), associations were limited to the caudate and putamen. Longitudinally, NfL predicted subsequent occipital gray matter atrophy and widespread white matter reduction, both before and after correction for other predictors of disease progression.

CONCLUSIONS

These findings highlight the value of NfL as a dynamic marker of brain atrophy and, more generally, provide further evidence of the strong association between plasma NfL level, a candidate blood biomarker, and pathologic neuronal change.

Magnetic Resonance Imaging in Huntington's Disease

Magnetic resonance imaging (MRI) is a noninvasive technique used routinely to image the body in both clinical and research settings. Through the manipulation of radio waves and static field gradients, MRI uses the principle of nuclear magnetic resonance to produce images with high spatial resolution, appropriate for the investigation of brain structure and function.

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.