External evaluation of a deep learning-based approach for automated brain volumetry in patients with huntington's disease.

A crucial step in the clinical adaptation of an AI-based tool is an external, independent validation. The aim of this study was to investigate brain atrophy in patients with confirmed, progressed Huntington's disease using a certified software for automated volumetry and to compare the results with the manual measurement methods used in clinical practice as well as volume calculations of the caudate nuclei based on manual segmentations. Twenty-two patients were included retrospectively, consisting of eleven patients with Huntington's disease and caudate nucleus atrophy and an age- and sex-matched control group. To quantify caudate head atrophy, the frontal horn width to intercaudate distance ratio and the intercaudate distance to inner table width ratio were obtained. The software mdbrain was used for automated volumetry. Manually measured ratios and automatically measured volumes of the groups were compared using two-sample t-tests. Pearson correlation analyses were performed. The relative difference between automatically and manually determined volumes of the caudate nuclei was calculated. Both ratios were significantly different between the groups. The automatically and manually determined volumes of the caudate nuclei showed a high level of agreement with a mean relative discrepancy of - 2.3 ± 5.5%. The Huntington's disease group showed significantly lower volumes in a variety of supratentorial brain structures. The highest degree of atrophy was shown for the caudate nucleus, putamen, and pallidum (all p < .0001). The caudate nucleus volume and the ratios were found to be strongly correlated in both groups. In conclusion, in patients with progressed Huntington's disease, it was shown that the automatically determined caudate nucleus volume correlates strongly with measured ratios commonly used in clinical practice. Both methods allowed clear differentiation between groups in this collective. The software additionally allows radiologists to more objectively assess the involvement of a variety of brain structures that are less accessible to standard semiquantitative methods.

Optimizing Screening for Intrastriatal Interventions in Huntington's Disease Using Predictive Models.

BACKGROUND: Intrastriatal delivery of potential therapeutics in Huntington's disease (HD) requires sufficient caudate and putamen volumes. Currently, volumetric magnetic resonance imaging is rarely done in clinical practice, and these data are not available in large research cohorts such as Enroll-HD. OBJECTIVE: The objective of this study was to investigate whether predictive models can accurately classify HD patients who exceed caudate and putamen volume thresholds required for intrastriatal therapeutic interventions. METHODS: We obtained and merged data for 1374 individuals across three HD cohorts: IMAGE-HD, PREDICT-HD, and TRACK-HD/TRACK-ON. We imputed missing data for clinical variables with >72% non-missing values and used the model-building algorithm BORUTA to identify the 10 most important variables. A random forest algorithm was applied to build a predictive model for putamen volume >2500 mm3 and caudate volume >2000 mm3 bilaterally. Using the same 10 predictors, we constructed a logistic regression model with predictors significant at P < 0.05. RESULTS: The random forest model with 1000 trees and minimal terminal node size of 5 resulted in 83% area under the curve (AUC). The logistic regression model retaining age, CAG repeat size, and symbol digit modalities test-correct had 85.1% AUC. A probability cutoff of 0.8 resulted in 5.4% false positive and 66.7% false negative rates. CONCLUSIONS: Using easily obtainable clinical data and machine learning-identified initial predictor variables, random forest, and logistic regression models can successfully identify people with sufficient striatal volumes for inclusion cutoffs. Adopting these models in prescreening could accelerate clinical trial enrollment in HD and other neurodegenerative disorders when volume cutoffs are necessary enrollment criteria. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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.

Identifying and verifying Huntington's disease subtypes: Clinical features, neuroimaging, and cytokine changes.

AIMS: Huntington's disease (HD) is a progressive neurodegenerative disorder with heterogeneous clinical manifestations. Identifying distinct clinical clusters and their relevant biomarkers could elucidate the underlying disease pathophysiology. METHODS: Following the Enroll-HD program initiated in 2018.09, we have recruited 104 HD patients (including 21 premanifest) and 31 health controls at Beijing Tiantan Hospital. Principal components analysis and k-means cluster analysis were performed to determine HD clusters. Chi-square test, one-way ANOVA, and covariance were used to identify features among these clusters. Furthermore, plasma cytokines levels and brain structural imaging were used as biomarkers to delineate the clinical features of each cluster. RESULTS: Three clusters were identified. Cluster 1 demonstrated the most severe motor and nonmotor symptoms except for chorea, the lowest whole brain volume, the plasma levels of IL-2 were higher and significantly associated with cluster 1. Cluster 2 was characterized with the most severe chorea and the largest pallidum volume. Cluster 3 had the most benign motor symptoms but moderate psychiatric problems. CONCLUSION: We have identified three HD clusters via clinical manifestations with distinct biomarkers. Our data shed light on better understanding about the pathophysiology of HD.

Disentangling the neurobiological bases of temporal impulsivity in Huntington's disease.

BACKGROUND: Despite its impact on daily life, impulsivity in Huntington's disease (HD) is understudied as a neuropsychiatric symptom. Our aim is to characterize temporal impulsivity in HD and to disentangle the white matter correlate associated with impulsivity. METHODS: Forty-seven HD individuals and 36 healthy controls were scanned and evaluated for temporal impulsivity using a delay-discounting (DD) task and complementary Sensitivity to Punishment and Sensitivity to Reward Questionnaire. Diffusion tensor imaging was employed to characterize the structural connectivity of three limbic tracts: the uncinate fasciculus (UF), the accumbofrontal tract (NAcc-OFC), and the dorsolateral prefrontal cortex connectig the caudate nucleus (DLPFC-cn). Multiple linear regression analyses were applied to analyze the relationship between impulsive behavior and white matter microstructural integrity. RESULTS: Our results revealed altered structural connectivity in the DLPC-cn, the NAcc-OFC and the UF in HD individuals. At the same time, the variability in structural connectivity of these tracts was associated with the individual differences in temporal impulsivity. Specifically, increased structural connectivity in the right NAcc-OFC and reduced connectivity in the left UF were associated with higher temporal impulsivity scores. CONCLUSIONS: The present findings highlight the importance of investigating the spectrum of temporal impulsivity in HD. As, while less prevalent than other psychiatric features, this symptom is still reported to significantly impact the quality of life of patients and caregivers. This study provides evidence that individual differences observed in temporal impulsivity may be explained by variability in limbic frontostriatal tracts, while shedding light on the role of sensitivity to reward in modulating impulsive behavior through the selection of immediate rewards.

Diffusion MRI marks progressive alterations in fiber integrity in the zQ175DN mouse model of Huntington's disease.

Huntington's disease (HD) is a progressive neurodegenerative disease affecting motor and cognitive abilities. Multiple studies have found white matter anomalies in HD-affected humans and animal models of HD. The identification of sensitive white-matter-based biomarkers in HD animal models will be important in understanding disease mechanisms and testing the efficacy of therapeutic interventions. Here we investigated the progression of white matter deficits in the knock-in zQ175DN heterozygous (HET) mouse model of HD at 3, 6 and 11 months of age (M), reflecting different states of phenotypic progression. We compared findings from traditional diffusion tensor imaging (DTI) and advanced fixel-based analysis (FBA) diffusion metrics for their sensitivity in detecting white matter anomalies in the striatum, motor cortex, and segments of the corpus callosum. FBA metrics revealed progressive and widespread reductions of fiber cross-section and fiber density in myelinated bundles of HET mice. The corpus callosum genu was the most affected structure in HET mice at 6 and 11 M based on the DTI and FBA metrics, while the striatum showed the earliest progressive differences starting at 3 M based on the FBA metrics. Overall, FBA metrics detected earlier and more prominent alterations in myelinated fiber bundles compared to the DTI metrics. Luxol fast blue staining showed no loss in myelin density, indicating that diffusion anomalies could not be explained by myelin reduction but diffusion anomalies in HET mice were accompanied by increased levels of neurofilament light chain protein at 11 M. Altogether, our findings reveal progressive alterations in myelinated fiber bundles that can be measured using diffusion MRI, representing a candidate noninvasive imaging biomarker to study phenotype progression and the efficacy of therapeutic interventions in zQ175DN mice. Moreover, our study exposed higher sensitivity of FBA than DTI metrics, suggesting a potential benefit of adopting these advanced metrics in other contexts, including biomarker development in humans.

Characterizing differences in retinal and choroidal microvasculature and structure in individuals with Huntington's Disease compared to healthy controls: A cross-sectional prospective study.

OBJECTIVE: To characterize retinal and choroidal microvascular and structural changes in patients who are gene positive for mutant huntingtin protein (mHtt) with symptoms of Huntington's Disease (HD). METHODS: This study is a cross-sectional comparison of patients who are gene positive for mHtt and exhibit symptoms of HD, either motor manifest or prodromal (HD group), and cognitively normal individuals without a family history of HD (control group). HD patients were diagnosed by Duke movement disorder neurologists based on the Unified Huntington's Disease Rating Scale (UHDRS). Fovea and optic nerve centered OCT and OCTA images were captured using Zeiss Cirrus HD-5000 with AngioPlex. Outcome metrics included central subfield thickness (CST), peripapillary retinal nerve fiber layer (pRNFL) thickness, ganglion cell-inner plexiform layer (GCIPL) thickness, and choroidal vascularity index (CVI) on OCT, and foveal avascular zone (FAZ) area, vessel density (VD), perfusion density (PD), capillary perfusion density (CPD), and capillary flux index (CFI) on OCTA. Generalized estimating equation (GEE) models were used to account for inter-eye correlation. RESULTS: Forty-four eyes of 23 patients in the HD group and 77 eyes of 39 patients in the control group were analyzed. Average GCIPL thickness and FAZ area were decreased in the HD group compared to controls (p = 0.001, p < 0.001). No other imaging metrics were significantly different between groups. CONCLUSIONS: Patients in the HD group had decreased GCIPL thickness and smaller FAZ area, highlighting the potential use of retinal biomarkers in detecting neurodegenerative changes in HD.

Baseline Large-Scale Network Dynamics Associated with Disease Progression in Huntington's Disease.

BACKGROUND: Huntington's disease (HD) is a genetically determined disease with motor, cognitive, and neuropsychiatric disorders. However, the links between clinical progression and disruptions to dynamics in motor and cognitive large-scale networks are not well established. OBJECTIVE: To investigate changes in dynamic and static large-scale networks using an established tool of disease progression in Huntington's disease, the composite Unified Huntington's Disease Rating Scale (cUHDRS). METHODS: Sixty-four mutation carriers were included. Static and dynamic baseline functional connectivity as well as topological features were correlated to 2-year follow-up clinical assessments using the cUHDRS. RESULTS: Decline in cUHDRS scores was associated with higher connectivity between frontal default-mode and motor networks, whereas higher connectivity in posterior, mainly visuospatial regions was associated with a smaller decline in cUHDRS scores. CONCLUSIONS: Structural disruptions in HD were evident both in posterior parietal/occipital and frontal motor regions, with reciprocal increases in functional connectivity. However, although higher visuospatial network connectivity was tied to a smaller cUHDRS decline, increased motor and frontal default-mode connections were linked to a larger cUHDRS decreases. Therefore, divergent functional compensation mechanisms might be at play in the clinical evolution of HD.

The shape of things to come. Mapping spatiotemporal progression of striatal morphology in Huntington disease: The IMAGE-HD study.

Mapping the spatiotemporal progression of neuroanatomical change in Huntington's Disease (HD) is fundamental to the development of bio-measures for prognostication. Statistical shape analysis to measure the striatum has been performed in HD, however there have been a limited number of longitudinal studies. To address these limitations, we utilised the Spherical Harmonic Point Distribution Method (SPHARM-PDM) to generate point distribution models of the striatum in individuals, and used linear mixed models to test for localised shape change over time in pre-manifest HD (pre-HD), symp-HD (symp-HD) and control individuals. Longitudinal MRI scans from the IMAGE-HD study were used (baseline, 18 and 30 months). We found significant differences in the shape of the striatum between groups. Significant group-by-time interaction was observed for the putamen bilaterally, but not for caudate. A differential rate of shape change between groups over time was observed, with more significant deflation in the symp-HD group in comparison with the pre-HD and control groups. CAG repeats were correlated with bilateral striatal shape in pre-HD and symp-HD. Robust statistical analysis of the correlates of striatal shape change in HD has confirmed the suitability of striatal morphology as a potential biomarker correlated with CAG-repeat length, and potentially, an endophenotype.

Detection of proteomic alterations at different stages in a Huntington's disease mouse model via matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) imaging.

Huntington's disease (HD) is a progressive and irreversible neurodegenerative disease leading to the inability to carry out daily activities and for which no cure exists. The underlying mechanisms of the disease have not been fully elucidated yet. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) allows the spatial information of proteins to be obtained upon the tissue sections without homogenisation. In this study, we aimed to examine proteomic alterations in the brain tissue of an HD mouse model with MALDI-MSI coupled to LC-MS/MS system. We used 3-, 6- and 12-month-old YAC128 mice representing pre-stage, mild stage and pathological stage of the HD and their non-transgenic littermates, respectively. The intensity levels of 89 proteins were found to be significantly different in YAC128 in comparison to their control mice in the pre-stage, 83 proteins in the mild stage, and 82 proteins in the pathological stage. Among them, Tau, EF2, HSP70, and NogoA proteins were validated with western blot analysis. In conclusion, the results of this study have provided remarkable new information about the spatial proteomic alterations in the HD mouse model, and we suggest that MALDI-MSI is an excellent technique for identifying such regional proteomic changes and could offer new perspectives in examining complex diseases.

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.

Mixed longitudinal and cross-sectional analyses of deep gray matter and white matter using diffusion weighted images in premanifest and manifest Huntington's disease.

Changes in the brain of patients with Huntington's disease (HD) begin years before clinical onset, so it remains critical to identify biomarkers to track these early changes. Metrics derived from tensor modeling of diffusion-weighted MRIs (DTI), that indicate the microscopic brain structure, can add important information to regional volumetric measurements. This study uses two large-scale longitudinal, multicenter datasets, PREDICT-HD and IMAGE-HD, to trace changes in DTI of HD participants with a broad range of CAP scores (a product of CAG repeat expansion and age), including those with pre-manifest disease (i.e., prior to clinical onset). Utilizing a fully automated data-driven approach to study the whole brain divided in regions of interest, we traced changes in DTI metrics (diffusivity and fractional anisotropy) versus CAP scores, using sigmoidal and linear regression models. We identified points of inflection in the sigmoidal regression using change-point analysis. The deep gray matter showed more evident and earlier changes in DTI metrics over CAP scores, compared to the deep white matter. In the deep white matter, these changes were more evident and occurred earlier in superior and posterior areas, compared to anterior and inferior areas. The curves of mean diffusivity vs. age of HD participants within a fixed CAP score were different from those of controls, indicating that the disease has an additional effect to age on the microscopic brain structure. These results show the regional and temporal vulnerability of the white matter and deep gray matter in HD, with potential implications for experimental therapeutics.

Hippocampal morphology in Huntington's disease, implications for plasticity and pathogenesis: The IMAGE-HD study.

While striatal changes in Huntington's Disease (HD) are well established, few studies have investigated changes in the hippocampus, a key neuronal hub. Using MRI scans obtained from the IMAGE-HD study, hippocampi were manually traced and then analysed with the Spherical Harmonic Point Distribution Method (SPHARM-PDM) in 36 individuals with presymptomatic-HD, 37 with early symptomatic-HD, and 36 healthy matched controls. There were no significant differences in overall hippocampal volume between groups. Interestingly we found decreased bilateral hippocampal volume in people with symptomatic-HD who took selective serotonin reuptake inhibitors compared to those who did not, despite no significant differences in anxiety, depressive symptoms, or motor incapacity between the two groups. In symptomatic-HD, there was also significant shape deflation in the right hippocampal head, showing the utility of using manual tracing and SPHARM-PDM to characterise subtle shape changes which may be missed by other methods. This study confirms previous findings of the lack of hippocampal volumetric differentiation in presymptomatic-HD and symptomatic-HD compared to controls. We also find novel shape and volume findings in those with symptomatic-HD, especially in relation to decreased hippocampal volume in those treated with SSRIs.

Neuroimaging biomarkers in Huntington's disease: Preparing for a new era of therapeutic development.

BACKGROUND: A critical challenge for Huntington's disease (HD) clinical trials in disease modification is the definition of endpoints that can capture change when clinical signs are subtle/non-existent. Reliable biomarkers are therefore urgently needed to facilitate drug development by allowing the enrichment of clinical trial populations and providing measures of benefit that can support the establishment of efficacy. METHODS: By systematically examining the published literature on HD neuroimaging biomarker studies, we sought to advance knowledge to guide the validation of neuroimaging biomarkers. We started by reviewing both cross-sectional and longitudinal studies and then conducted an in-depth review to make quantitative comparisons between biomarkers using data only from longitudinal studies with samples sizes larger than ten participants in PET studies or 30 participants in MRI studies. RESULTS: From a total of 2202 publications initially identified, we included 32 studies, 19 of which underwent in-depth comparative review. The majority of included studies used various MRI-based methods (manual to automatic) to longitudinally assess either the volume of the putamen or the caudate, which have been shown to undergo significant structural change during HD natural history. CONCLUSION: Despite the impressively large number of neuroimaging biomarker studies, only a small number of adequately designed studies met our criteria. Among these various biomarkers, MRI-based volumetric analyses of the caudate and putamen are currently the best validated for use in the disease phase before clinical motor diagnosis. A biomarker that can be used to demonstrate a disease-modifying effect is still missing.

Cerebrospinal Fluid Flow in Patients with Huntington's Disease.

OBJECTIVE: Investigations of cerebrospinal fluid (CSF) flow aberrations in Huntington's disease (HD) are of growing interest, as impaired CSF flow may contribute to mutant Huntington retention and observed heterogeneous responsiveness to intrathecally administered therapies. METHOD: We assessed net cerebral aqueduct CSF flow and velocity in 29 HD participants (17 premanifest and 12 manifest) and 51 age- and sex matched non-HD control participants using 3-Tesla magnetic resonance imaging methods. Regression models were applied to test hypotheses regarding: (i) net CSF flow and cohort, (ii) net CSF flow and disease severity (CAP-score), and (iii) CSF volume after correcting for age and sex. RESULTS: Group-wise analyses support a decrease in net CSF flow in HD (mean 0.14 ± 0.27 mL/min) relative to control (mean 0.32 ± 0.20 mL/min) participants (p = 0.02), with lowest flow in the manifest HD cohort (mean 0.04 ± 0.25 mL/min). This finding was explained by hyperdynamic CSF movement, manifesting as higher caudal systolic CSF flow velocity and higher diastolic cranial CSF flow velocity across the cardiac cycle, in HD (caudal flow: 0.17 ± 0.07 mL/s, cranial flow: 0.14 ± 0.08 mL/s) compared to control (caudal flow: 0.13 ± 0.06 mL/s, cranial flow: 0.11 ± 0.04 mL/s) participants. A positive correlation between cranial diastolic flow and disease severity was observed (p = 0.02). INTERPRETATIONS: Findings support aqueductal CSF flow dynamics changing with disease severity in HD. These accelerated changes are consistent with changes observed over the typical adult lifespan, and may have relevance to mutant Huntington retention and intrathecally administered therapeutics responsiveness. ANN NEUROL 2023;94:885-894.

Selective perforant-pathway atrophy in Huntington disease: MRI analysis of hippocampal subfields.

INTRODUCTION: While individuals with Huntington disease (HD) show memory impairment that indicates hippocampal dysfunction, the available literature does not consistently identify structural evidence for involvement of the whole hippocampus but rather suggests that hippocampal atrophy may be confined to certain hippocampal subregions. METHODS: We processed T1-weighted MRI from IMAGE-HD study using FreeSurfer 7.0 and compared the volumes of the hippocampal subfields among 36 early motor symptomatic (symp-HD), 40 pre-symptomatic (pre-HD), and 36 healthy control individuals across three timepoints over 36 months. RESULTS: Mixed-model analyses revealed significantly lower subfield volumes in symp-HD, compared with pre-HD and control groups, in the subicular regions of the perforant-pathway: presubiculum, subiculum, dentate gyrus, tail, and right molecular layer. These adjoining subfields aggregated into a single principal component, which demonstrated an accelerated rate of atrophy in the symp-HD. Volumes between pre-HD and controls did not show any significant difference. In the combined HD groups, CAG repeat length and disease burden score were associated with presubiculum, molecular layer, tail, and perforant-pathway subfield volumes. Hippocampal left tail and perforant-pathway subfields were associated with motor onset in the pre-HD group. CONCLUSIONS: Hippocampal subfields atrophy in early symptomatic HD affects key regions of the perforant-pathway, which may implicate the distinctive memory impairment at this stage of illness. Their volumetric associations with genetic and clinical markers suggest the selective susceptibility of these subfields to mutant Huntingtin and disease progression.

Study protocol of IMAGINE-HD: Imaging iron accumulation and neuroinflammation with 7T-MRI + CSF in Huntington's disease.

INTRODUCTION: Strong evidence suggests a significant role for iron accumulation in the brain in addition to the well-documented neurodegenerative aspects of Huntington's disease (HD). The putative mechanisms by which iron is linked to the HD pathogenesis are multiple, including oxidative stress, ferroptosis and neuroinflammation. However, no previous study in a neurodegenerative disease has linked the observed increase of brain iron accumulation as measured by MRI with well-established cerebrospinal fluid (CSF) and blood biomarkers for iron accumulation, or with associated processes such as neuroinflammation. This study is designed to link quantitative data from iron levels and neuroinflammation metabolites obtained from 7T MRI of HD patients, with specific and well-known clinical biofluid markers for iron accumulation, neurodegeneration and neuroinflammation. Biofluid markers will provide quantitative measures of overall iron accumulation, neurodegeneration and neuroinflammation, while MRI measurements on the other hand will provide quantitative spatial information on brain pathology, neuroinflammation and brain iron accumulation, which will be linked to clinical outcome measures. METHODS: This is an observational cross-sectional study, IMAGINE-HD, in HD gene expansion carriers and healthy controls. We include premanifest HD gene expansion carriers and patients with manifest HD in an early or moderate stage. The study includes a 7T MRI scan of the brain, clinical evaluation, motor, functional, and neuropsychological assessments, and sampling of CSF and blood for the detection of iron, neurodegenerative and inflammatory markers. Quantitative Susceptibility Maps will be reconstructed using T2* weighted images to quantify brain iron levels and Magnetic Resonance Spectroscopy will be used to obtain information about neuroinflammation by measuring cell-specific intracellular metabolites' level and diffusion. Age and sex matched healthy subjects are included as a control group. DISCUSSION: Results from this study will provide an important basis for the evaluation of brain iron levels and neuroinflammation metabolites as an imaging biomarker for disease stage in HD and their relationship with the salient pathomechanisms of the disease on the one hand, and with clinical outcome on the other.

Longitudinal investigation of changes in resting-state co-activation patterns and their predictive ability in the zQ175 DN mouse model of Huntington's disease.

Huntington's disease (HD) is a neurodegenerative disorder caused by expanded (≥ 40) glutamine-encoding CAG repeats in the huntingtin gene, which leads to dysfunction and death of predominantly striatal and cortical neurons. While the genetic profile and clinical signs and symptoms of the disease are better known, changes in the functional architecture of the brain, especially before the clinical expression becomes apparent, are not fully and consistently characterized. In this study, we sought to uncover functional changes in the brain in the heterozygous (HET) zQ175 delta-neo (DN) mouse model at 3, 6, and 10 months of age, using resting-state functional magnetic resonance imaging (RS-fMRI). This mouse model shows molecular, cellular and circuitry alterations that worsen through age. Motor function disturbances are manifested in this model at 6 and 10 months of age. Specifically, we investigated, longitudinally, changes in co-activation patterns (CAPs) that are the transient states of brain activity constituting the resting-state networks (RSNs). Most robust changes in the temporal properties of CAPs occurred at the 10-months time point; the durations of two anti-correlated CAPs, characterized by simultaneous co-activation of default-mode like network (DMLN) and co-deactivation of lateral-cortical network (LCN) and vice-versa, were reduced in the zQ175 DN HET animals compared to the wild-type mice. Changes in the spatial properties, measured in terms of activation levels of different brain regions, during CAPs were found at all three ages and became progressively more pronounced at 6-, and 10 months of age. We then assessed the cross-validated predictive power of CAP metrics to distinguish HET animals from controls. Spatial properties of CAPs performed significantly better than the chance level at all three ages with 80% classification accuracy at 6 and 10 months of age.

Pearls & Oy-sters: Huntington Disease Presenting as Primary Progressive Aphasia: A Case of Semantics.

We present a case of semantic variant primary progressive aphasia as the presenting feature in a patient with Huntington disease (HD). The patient initially developed progressive language impairment including impaired naming and object knowledge and single-word comprehension and then developed chorea and behavioral changes. An MRI of the brain showed left anterior temporal lobe and hippocampal atrophy. A neurologic FDG PET/CT showed reduced metabolism in the head of the left caudate nucleus. Huntingtin gene testing revealed an expansion of 39 CAG repeats in 1 allele. This case outlines the substantial overlap between the clinical presentation of HD and frontotemporal lobar degeneration syndromes and provides commentary on the investigation of these neurodegenerative diseases.