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.

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.

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.

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.

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.

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.

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.

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.

MEG Adaptation Resolves the Spatiotemporal Characteristics of Face-Sensitive Brain Responses.

An unresolved goal in face perception is to identify brain areas involved in face processing and simultaneously understand the timing of their involvement. Currently, high spatial resolution imaging techniques identify the fusiform gyrus as subserving processing of invariant face features relating to identity. High temporal resolution imaging techniques localize an early latency evoked component-the N/M170-as having a major generator in the fusiform region; however, this evoked component is not believed to be associated with the processing of identity. To resolve this, we used novel magnetoencephalographic beamformer analyses to localize cortical regions in humans spatially with trial-by-trial activity that differentiated faces and objects and to interrogate their functional sensitivity by analyzing the effects of stimulus repetition. This demonstrated a temporal sequence of processing that provides category-level and then item-level invariance. The right fusiform gyrus showed adaptation to faces (not objects) at ∼150 ms after stimulus onset regardless of face identity; however, at the later latency of ∼200-300 ms, this area showed greater adaptation to repeated identity faces than to novel identities. This is consistent with an involvement of the fusiform region in both early and midlatency face-processing operations, with only the latter showing sensitivity to invariant face features relating to identity. SIGNIFICANCE STATEMENT: Neuroimaging techniques with high spatial-resolution have identified brain structures that are reliably activated when viewing faces and techniques with high temporal resolution have identified the time-varying temporal signature of the brain's response to faces. However, until now, colocalizing face-specific mechanisms in both time and space has proven notoriously difficult. Here, we used novel magnetoencephalographic analysis techniques to spatially localize cortical regions with trial-by-trial temporal activity that differentiates between faces and objects and to interrogate their functional sensitivity by analyzing effects of stimulus repetition on the time-locked signal. These analyses confirm a role for the right fusiform region in early to midlatency responses consistent with face identity processing and convincingly deliver upon magnetoencephalography's promise to resolve brain signals in time and space simultaneously.

Visuospatial Processing Deficits Linked to Posterior Brain Regions in Premanifest and Early Stage Huntington's Disease.

OBJECTIVES: Visuospatial processing deficits have been reported in Huntington's disease (HD). To date, no study has examined associations between visuospatial cognition and posterior brain findings in HD. METHODS: We compared 119 premanifest (55> and 64<10.8 years to expected disease onset) and 104 early symptomatic (59 stage-1 and 45 stage-2) gene carriers, with 110 controls on visual search and mental rotation performance at baseline and 12 months. In the disease groups, we also examined associations between task performance and disease severity, functional capacity and structural brain measures. RESULTS: Cross-sectionally, there were strong differences between all disease groups and controls on visual search, and between diagnosed groups and controls on mental rotation accuracy. Only the premanifest participants close to onset took longer than controls to respond correctly to mental rotation. Visual search negatively correlated with disease burden and motor symptoms in diagnosed individuals, and positively correlated with functional capacity. Mental rotation ("same") was negatively correlated with motor symptoms in stage-2 individuals, and positively correlated with functional capacity. Visual search and mental rotation were associated with parieto-occipital (pre-/cuneus, calcarine, lingual) and temporal (posterior fusiform) volume and cortical thickness. Longitudinally, visual search deteriorated over 12 months in stage-2 individuals, with no evidence of declines in mental rotation. CONCLUSIONS: Our findings provide evidence linking early visuospatial deficits to functioning and posterior cortical dysfunction in HD. The findings are important since large research efforts have focused on fronto-striatal mediated cognitive changes, with little attention given to aspects of cognition outside of these areas. (JINS, 2016, 22, 595-608).

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.

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.

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.

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.

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.

Altered iron and myelin in premanifest Huntington's Disease more than 20 years before clinical onset: Evidence from the cross-sectional HD Young Adult Study.

BACKGROUND: Pathological processes in Huntington's disease (HD) begin many years prior to symptom onset. Recently we demonstrated that in a premanifest cohort approximately 24 years from predicted disease onset, despite intact function, there was evidence of subtle neurodegeneration. Here, we use novel imaging techniques to determine whether macro- and micro-structural changes can be detected across the whole-brain in the same cohort. METHODS: 62 premanifest HD (PreHD) and 61 controls from the HD Young Adult Study (HD-YAS) were included. Grey and white matter volume, diffusion weighted imaging (DWI) measures of white matter microstructure, multiparametric maps (MPM) estimating myelin and iron content from magnetization transfer (MT), proton density (PD), longitudinal relaxation (R1) and effective transverse relaxation (R2*), and myelin g-ratio were examined. Group differences between PreHD and controls were assessed; associations between all imaging metrics and disease burden and CSF neurofilament light (NfL) were also performed. Volumetric and MPM results were corrected at a cluster-wise value of familywise error (FWE) 0.05. Diffusion and g-ratio results were corrected via threshold-free cluster enhancement at FWE 0.05. FINDINGS: We showed significantly increased R1 and R2*, suggestive of increased iron, in the putamen, globus pallidum and external capsule of PreHD participants. There was also a significant association between lower cortical R2*, suggestive of reduced myelin or iron, and higher CSF NfL in the frontal lobe and the parieto-occipital cortices. No other results were significant at corrected levels. INTERPRETATION: Increased iron in subcortical structures and the surrounding white matter is a feature of very early PreHD. Furthermore, increases in CSF NfL were linked to microstructural changes in the posterior parietal-occipital cortex, a region previously shown to undergo some of the earliest cortical changes in HD. These findings suggest that disease related process are occurring in both subcortical and cortical regions more than 20 years from predicted disease onset.

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.