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

Neuroinflammation and the role of epigenetic-based therapies for Huntington's disease management: the new paradigm

Huntington's disease (HD) is an inherited, autosomal, neurodegenerative ailment that affects the striatum of the brain. Despite its debilitating effect on its patients, there is no proven cure for HD management as of yet. Neuroinflammation, excitotoxicity, and environmental factors have been reported to influence the regulation of gene expression by modifying epigenetic mechanisms. Aside focusing on the etiology, changes in epigenetic mechanisms have become a crucial factor influencing the interaction between HTT protein and epigenetically transcribed genes involved in neuroinflammation and HD. This review presents relevant literature on epigenetics with special emphasis on neuroinflammation and HD. It summarizes pertinent research on the role of neuroinflammation and post-translational modifications of chromatin, including DNA methylation, histone modification, and miRNAs. To achieve this about 1500 articles were reviewed via databases like PubMed, ScienceDirect, Google Scholar, and Web of Science. They were reduced to 534 using MeSH words like 'epigenetics, neuroinflammation, and HD' coupled with Boolean operators. Results indicated that major contributing factors to the development of HD such as mitochondrial dysfunction, excitotoxicity, neuroinflammation, and apoptosis are affected by epigenetic alterations. However, the association between neuroinflammation-altered epigenetics and the reported transcriptional changes in HD is unknown. Also, the link between epigenetically dysregulated genomic regions and specific DNA sequences suggests the likelihood that transcription factors, chromatin-remodeling proteins, and enzymes that affect gene expression are all disrupted simultaneously. Hence, therapies that target pathogenic pathways in HD, including neuroinflammation, transcriptional dysregulation, triplet instability, vesicle trafficking dysfunction, and protein degradation, need to be developed.

Graph methods to infer spatial disturbances: Application to Huntington's Disease's speech

OBJECTIVE

Huntington's Disease (HD) is an inherited neurodegenerative disease caused by the mutation of the Htt gene, impacting all aspects of living and functioning. Among cognitive disabilities, spatial capacities are impaired, but their monitoring remains scarce as limited by lengthy experts' assessments. Language offers an alternative medium to evaluate patients' performance in HD. Yet, its capacities to assess HD's spatial abilities are unknown. Here, we aimed to bring proof-of-concept that HD's spatial deficits can be assessed through speech.

METHODS

We developed the Spatial Description Model to graphically represent spatial relations described during the Cookie Theft Picture (CTP) task. We increased the sensitivity of our model by using only sentences with spatial terms, unlike previous studies in Alzheimer's disease. 78 carriers of the mutant Htt, including 56 manifest and 22 premanifest individuals, as well as 25 healthy controls were included from the BIOHD & (NCT01412125) & Repair-HD (NCT03119246) cohorts. The convergence and divergence of the model were validated using the SelfCog battery.

RESULTS

Our Spatial Description Model was the only one among the four assessed approaches, revealing that individuals with manifest HD expressed fewer spatial relations and engaged in less spatial exploration compared to healthy controls. Their graphs correlated with both visuospatial and language SelfCog performances, but not with motor, executive nor memory functions.

CONCLUSIONS

We provide the proof-of-concept using our Spatial Description Model that language can grasp HD patient's spatial disturbances. By adding spatial capabilities to the panel of functions tested by the language, it paves the way for eventual remote clinical application.

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.

Selective vulnerability of layer 5a corticostriatal neurons in Huntington's disease

The properties of the cell types that are selectively vulnerable in Huntington's disease (HD) cortex, the nature of somatic CAG expansions of mHTT in these cells, and their importance in CNS circuitry have not been delineated. Here, we employed serial fluorescence-activated nuclear sorting (sFANS), deep molecular profiling, and single-nucleus RNA sequencing (snRNA-seq) of motor-cortex samples from thirteen predominantly early stage, clinically diagnosed HD donors and selected samples from cingulate, visual, insular, and prefrontal cortices to demonstrate loss of layer 5a pyramidal neurons in HD. Extensive mHTT CAG expansions occur in vulnerable layer 5a pyramidal cells, and in Betz cells, layers 6a and 6b neurons that are resilient in HD. Retrograde tracing experiments in macaque brains identify layer 5a neurons as corticostriatal pyramidal cells. We propose that enhanced somatic mHTT CAG expansion and altered synaptic function act together to cause corticostriatal disconnection and selective neuronal vulnerability in HD cerebral cortex.

Neuropathogenesis-on-chips for neurodegenerative diseases

Developing diagnostics and treatments for neurodegenerative diseases (NDs) is challenging due to multifactorial pathogenesis that progresses gradually. Advanced in vitro systems that recapitulate patient-like pathophysiology are emerging as alternatives to conventional animal-based models. In this review, we explore the interconnected pathogenic features of different types of ND, discuss the general strategy to modelling NDs using a microfluidic chip, and introduce the organoid-on-a-chip as the next advanced relevant model. Lastly, we overview how these models are being applied in academic and industrial drug development. The integration of microfluidic chips, stem cells, and biotechnological devices promises to provide valuable insights for biomedical research and developing diagnostic and therapeutic solutions for NDs.

Age- and region-dependent cortical excitability in the zQ175 Huntington disease mouse model

The neurodegenerative disorder, Huntington disease (HD), manifests as disorders of movement, cognition and mood. Although studies report abnormal corticostriatal synaptic function early in HD mouse models, less is known about cortical-cortical activity across brain regions and disease stages. Recently, we reported enhanced mesoscale spread of cortical responses to sensory stimulation in vivo at early-manifest stages of two HD mouse models. Here, we investigated cortical excitability of zQ175 HD-model mice compared to their wild-type littermates across different cell types, ages and/or cortical regions using ex vivo electrophysiology. Cortical pyramidal neurons (CPNs) in somatosensory cortex of zQ175 mice showed intrinsic hyper-excitability at 3-4 months, but hypo-excitability at early-manifest stage (8-9 months); reduced frequency of spontaneous excitatory postsynaptic currents (sEPSCs) was seen at both ages. In contrast, motor cortex CPNs in early-manifest zQ175 mice showed increased intrinsic excitability and sEPSC frequency. Large-amplitude excitatory discharges recorded from CPNs in early-manifest zQ175 mice showed increased frequency only in somatosensory cortex, suggesting the intrinsic hypo-excitability of these CPNs may be compensatory against cortical network hyper-excitability. Similarly, in early-manifest zQ175 mice, region-dependent differences were seen in fast-spiking interneurons (FSIs): somatosensory but not motor FSIs from early-manifest zQ175 mice had reduced intrinsic excitability. Moreover, CPNs showed decreased frequency of spontaneous inhibitory postsynaptic currents and increased excitatory-inhibitory (E-I) balance of evoked synaptic currents in somatosensory cortex. Aberrant large-amplitude discharges and reduced inhibitory drive may therefore underlie E-I imbalances that result in circuit changes and synaptic dysfunction in early-manifest 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.

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.

Antagonistic roles of canonical and Alternative-RPA in disease-associated tandem CAG repeat instability

Expansions of repeat DNA tracts cause >70 diseases, and ongoing expansions in brains exacerbate disease. During expansion mutations, single-stranded DNAs (ssDNAs) form slipped-DNAs. We find the ssDNA-binding complexes canonical replication protein A (RPA1, RPA2, and RPA3) and Alternative-RPA (RPA1, RPA3, and primate-specific RPA4) are upregulated in Huntington disease and spinocerebellar ataxia type 1 (SCA1) patient brains. Protein interactomes of RPA and Alt-RPA reveal unique and shared partners, including modifiers of CAG instability and disease presentation. RPA enhances in vitro melting, FAN1 excision, and repair of slipped-CAGs and protects against CAG expansions in human cells. RPA overexpression in SCA1 mouse brains ablates expansions, coincident with decreased ATXN1 aggregation, reduced brain DNA damage, improved neuron morphology, and rescued motor phenotypes. In contrast, Alt-RPA inhibits melting, FAN1 excision, and repair of slipped-CAGs and promotes CAG expansions. These findings suggest a functional interplay between the two RPAs where Alt-RPA may antagonistically offset RPA's suppression of disease-associated repeat expansions, which may extend to other DNA processes.

Selective Vulnerability of Layer 5a Corticostriatal Neurons in Huntington's Disease

The properties of the cell types that are selectively vulnerable in Huntington's disease (HD) cortex, the nature of somatic CAG expansions of mHTT in these cells, and their importance in CNS circuitry have not been delineated. Here we employed serial fluorescence activated nuclear sorting (sFANS), deep molecular profiling, and single nucleus RNA sequencing (snRNAseq) to demonstrate that layer 5a pyramidal neurons are vulnerable in primary motor cortex and other cortical areas of HD donors. Extensive mHTT -CAG expansions occur in vulnerable layer 5a pyramidal cells, and in Betz cells, layer 6a, layer 6b neurons that are resilient in HD. Retrograde tracing experiments in macaque brains identify the vulnerable layer 5a neurons as corticostriatal pyramidal cells. We propose that enhanced somatic mHTT -CAG expansion and altered synaptic function act together to cause corticostriatal disconnection and selective neuronal vulnerability in the HD cerebral cortex.

Ex vivo 100 μm isotropic diffusion MRI-based tractography of connectivity changes in the end-stage R6/2 mouse model of Huntington's disease

Background

Huntington's disease is a progressive neurodegenerative disorder. Brain atrophy, as measured by volumetric magnetic resonance imaging (MRI), is a downstream consequence of neurodegeneration, but microstructural changes within brain tissue are expected to precede this volumetric decline. The tissue microstructure can be assayed non-invasively using diffusion MRI, which also allows a tractographic analysis of brain connectivity.

Methods

We here used ex vivo diffusion MRI (11.7 T) to measure microstructural changes in different brain regions of end-stage (14 weeks of age) wild type and R6/2 mice (male and female) modeling Huntington's disease. To probe the microstructure of different brain regions, reduce partial volume effects and measure connectivity between different regions, a 100 μm isotropic voxel resolution was acquired.

Results

Although fractional anisotropy did not reveal any difference between wild-type controls and R6/2 mice, mean, axial, and radial diffusivity were increased in female R6/2 mice and decreased in male R6/2 mice. Whole brain streamlines were only reduced in male R6/2 mice, but streamline density was increased. Region-to-region tractography indicated reductions in connectivity between the cortex, hippocampus, and thalamus with the striatum, as well as within the basal ganglia (striatum-globus pallidus-subthalamic nucleus-substantia nigra-thalamus).

Conclusions

Biological sex and left/right hemisphere affected tractographic results, potentially reflecting different stages of disease progression. This proof-of-principle study indicates that diffusion MRI and tractography potentially provide novel biomarkers that connect volumetric changes across different brain regions. In a translation setting, these measurements constitute a novel tool to assess the therapeutic impact of interventions such as neuroprotective agents in transgenic models, as well as patients with Huntington's disease.

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.

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.

A new approach to digitized cognitive monitoring: validity of the SelfCog in Huntington's disease

Cognitive deficits represent a hallmark of neurodegenerative diseases, but evaluating their progression is complex. Most current evaluations involve lengthy paper-and-pencil tasks which are subject to learning effects dependent on the mode of response (motor or verbal), the countries' language or the examiners. To address these limitations, we hypothesized that applying neuroscience principles may offer a fruitful alternative. We thus developed the SelfCog, a digitized battery that tests motor, executive, visuospatial, language and memory functions in 15 min. All cognitive functions are tested according to the same paradigm, and a randomization algorithm provides a new test at each assessment with a constant level of difficulty. Here, we assessed its validity, reliability and sensitivity to detect decline in early-stage Huntington's disease in a prospective and international multilingual study (France, the UK and Germany). Fifty-one out of 85 participants with Huntington's disease and 40 of 52 healthy controls included at baseline were followed up for 1 year. Assessments included a comprehensive clinical assessment battery including currently standard cognitive assessments alongside the SelfCog. We estimated associations between each of the clinical assessments and SelfCog using Spearman's correlation and proneness to retest effects and sensitivity to decline through linear mixed models. Longitudinal effect sizes were estimated for each cognitive score. Voxel-based morphometry and tract-based spatial statistics analyses were conducted to assess the consistency between performance on the SelfCog and MRI 3D-T1 and diffusion-weighted imaging in a subgroup that underwent MRI at baseline and after 12 months. The SelfCog detected the decline of patients with Huntington's disease in a 1-year follow-up period with satisfactory psychometric properties. Huntington's disease patients are correctly differentiated from controls. The SelfCog showed larger effect sizes than the classical cognitive assessments. Its scores were associated with grey and white matter damage at baseline and over 1 year. Given its good performance in longitudinal analyses of the Huntington's disease cohort, it should likely become a very useful tool for measuring cognition in Huntington's disease in the future. It highlights the value of moving the field along the neuroscience principles and eventually applying them to the evaluation of all neurodegenerative diseases.

Advances in the neuroimaging of motor disorders

Neuroimaging is a valuable adjunct to the history and examination in the evaluation of motor system disorders. Conventional imaging with computed tomography or magnetic resonance imaging depicts important anatomic information and helps to identify imaging patterns which may support diagnosis of a specific motor disorder. Advanced imaging techniques can provide further detail regarding volume, functional, or metabolic changes occurring in nervous system pathology. This chapter is an overview of the advances in neuroimaging with particular emphasis on both standard and less well-known advanced imaging techniques and findings, such as diffusion tensor imaging or volumetric studies, and their application to specific motor disorders. In addition, it provides reference to emerging imaging biomarkers in motor system disorders such as Parkinson disease, amyotrophic lateral sclerosis, and Huntington disease, and briefly reviews the neuroimaging findings in different causes of myelopathy and peripheral nerve disorders.

Contribution of Glial Cells to Polyglutamine Diseases: Observations from Patients and Mouse Models

Neurodegenerative diseases are broadly characterized neuropathologically by the degeneration of vulnerable neuronal cell types in a specific brain region. The degeneration of specific cell types has informed on the various phenotypes/clinical presentations in someone suffering from these diseases. Prominent neurodegeneration of specific neurons is seen in polyglutamine expansion diseases including Huntington's disease (HD) and spinocerebellar ataxias (SCA). The clinical manifestations observed in these diseases could be as varied as the abnormalities in motor function observed in those who have Huntington's disease (HD) as demonstrated by a chorea with substantial degeneration of striatal medium spiny neurons (MSNs) or those with various forms of spinocerebellar ataxia (SCA) with an ataxic motor presentation primarily due to degeneration of cerebellar Purkinje cells. Due to the very significant nature of the degeneration of MSNs in HD and Purkinje cells in SCAs, much of the research has centered around understanding the cell autonomous mechanisms dysregulated in these neuronal cell types. However, an increasing number of studies have revealed that dysfunction in non-neuronal glial cell types contributes to the pathogenesis of these diseases. Here we explore these non-neuronal glial cell types with a focus on how each may contribute to the pathogenesis of HD and SCA and the tools used to evaluate glial cells in the context of these diseases. Understanding the regulation of supportive and harmful phenotypes of glia in disease could lead to development of novel glia-focused neurotherapeutics.

Pepinemab antibody blockade of SEMA4D in early Huntington's disease: a randomized, placebo-controlled, phase 2 trial

SIGNAL is a multicenter, randomized, double-blind, placebo-controlled phase 2 study (no. NCT02481674) established to evaluate pepinemab, a semaphorin 4D (SEMA4D)-blocking antibody, for treatment of Huntington's disease (HD). The trial enrolled a total of 265 HD gene expansion carriers with either early manifest (EM, n = 179) or late prodromal (LP, n = 86) HD, randomized (1:1) to receive 18 monthly infusions of pepinemab (n = 91 EM, 41 LP) or placebo (n = 88 EM, 45 LP). Pepinemab was generally well tolerated, with a relatively low frequency of serious treatment-emergent adverse events of 5% with pepinemab compared to 9% with placebo, including both EM and LP participants. Coprimary efficacy outcome measures consisted of assessments within the EM cohort of (1) a two-item HD cognitive assessment family comprising one-touch stockings of Cambridge (OTS) and paced tapping (PTAP) and (2) clinical global impression of change (CGIC). The differences between pepinemab and placebo in mean change (95% confidence interval) from baseline at month 17 for OTS were -1.98 (-4.00, 0.05) (one-sided P = 0.028), and for PTAP 1.43 (-0.37, 3.23) (one-sided P = 0.06). Similarly, because a significant treatment effect was not observed for CGIC, the coprimary endpoint, the study did not meet its prespecified primary outcomes. Nevertheless, a number of other positive outcomes and post hoc subgroup analyses-including additional cognitive measures and volumetric magnetic resonance imaging and fluorodeoxyglucose-positron-emission tomography imaging assessments-provide rationale and direction for the design of a phase 3 study and encourage the continued development of pepinemab in patients diagnosed with EM HD.

Neuroinflammation in Huntington's Disease: A Starring Role for Astrocyte and Microglia

Huntington's disease (HD) is a neurodegenerative genetic disorder caused by a CAG repeat expansion in the huntingtin gene. HD causes motor, cognitive, and behavioral dysfunction. Since no existing treatment affects the course of this disease, new treatments are needed. Inflammation is frequently observed in HD patients before symptom onset. Neuroinflammation, characterized by the presence of reactive microglia, astrocytes and inflammatory factors within the brain, is also detected early. However, in comparison to other neurodegenerative diseases, the role of neuroinflammation in HD is much less known. Work has been dedicated to altered microglial and astrocytic functions in the context of HD, but less attention has been given to glial participation in neuroinflammation. This review describes evidence of inflammation in HD patients and animal models. It also discusses recent knowledge on neuroinflammation in HD, highlighting astrocyte and microglia involvement in the disease and considering anti-inflammatory therapeutic approaches.

The progression rate of spinocerebellar ataxia type 3 varies with disease stage

BACKGROUND

In polyglutamine (polyQ) diseases, the identification of modifiers and the construction of prediction model for progression facilitate genetic counseling, clinical management and therapeutic interventions.

METHODS

Data were derived from the longest longitudinal study, with 642 examinations by International Cooperative Ataxia Rating Scale (ICARS) from 82 SCA3 participants. Using different time scales of disease duration, we performed multiple different linear, quadratic and piece-wise linear growth models to fit the relationship between ICARS scores and duration. Models comparison was employed to determine the best-fitting model according to goodness-of-fit tests, and the analysis of variance among nested models.

RESULTS

An acceleration was detected after 13 years of duration: ICARS scores progressed 2.445 (SE: 0.185) points/year before and 3.547 (SE: 0.312) points/year after this deadline. Piece-wise growth model fitted better to studied data than other two types of models. The length of expanded CAG repeat (CAGexp) in ATXN3 gene significantly influenced progression. Age at onset of gait ataxia (AOga), a proxy for aging process, was not an independent modifier but affected the correlation between CAGexp and progression. Additionally, gender had no significant effect on progression rate of ICARS. The piece-wise growth models were determined as the predictive models, and ICARS predictions from related models were available.

CONCLUSIONS

We first confirmed that ICARS progressed as a nonlinear pattern and varied according to different stages in SCA3. In addition to ATXN3 CAGexp, AOga or aging process regulated the progression by interacting with CAGexp.

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.

Arithmetic Word-Problem Solving as Cognitive Marker of Progression in Pre-Manifest and Manifest Huntington's Disease

BACKGROUND

Arithmetic word-problem solving depends on the interaction of several cognitive processes that may be affected early in the disease in gene-mutation carriers for Huntington's disease (HD).

OBJECTIVE

Our goal was to examine the pattern of performance of arithmetic tasks in premanifest and manifest HD, and to examine correlations between arithmetic task performance and other neuropsychological tasks.

METHODS

We collected data from a multicenter cohort of 165 HD gene-mutation carriers. The sample consisted of 31 premanifest participants: 16 far-from (>12 years estimated time to diagnosis; preHD-A) and 15 close-to (≤12 years estimated time to diagnosis; preHD-B), 134 symptomatic patients (early-mild HD), and 37 healthy controls (HC). We compared performance between groups and explored the associations between arithmetic word-problem solving and neuropsychological and clinical variables.

RESULTS

Total arithmetic word-problem solving scores were lower in preHD-B patients than in preHD-A (p < 0.05) patients and HC (p < 0.01). Early-mild HD patients had lower scores than preHD patients (p < 0.001) and HC (p < 0.001). Compared to HC, preHD and early-mild HD participants made more errors as trial complexity increased. Moreover, arithmetic word-problem solving scores were significantly associated with measures of global cognition (p < 0.001), frontal-executive functions (p < 0.001), attention (p < 0.001) visual working memory (p < 0.001), mental rotation (p < 0.001), and confrontation naming (p < 0.05).

CONCLUSION

Arithmetic word-problem solving is affected early in the course of HD and is related to deficient processes in frontal-executive and mentalizing-related processes.

Imaging Transcriptomics of Brain Disorders

Noninvasive neuroimaging is a powerful tool for quantifying diverse aspects of brain structure and function in vivo, and it has been used extensively to map the neural changes associated with various brain disorders. However, most neuroimaging techniques offer only indirect measures of underlying pathological mechanisms. The recent development of anatomically comprehensive gene expression atlases has opened new opportunities for studying the transcriptional correlates of noninvasively measured neural phenotypes, offering a rich framework for evaluating pathophysiological hypotheses and putative mechanisms. Here, we provide an overview of some fundamental methods in imaging transcriptomics and outline their application to understanding brain disorders of neurodevelopment, adulthood, and neurodegeneration. Converging evidence indicates that spatial variations in gene expression are linked to normative changes in brain structure during age-related maturation and neurodegeneration that are in part associated with cell-specific gene expression markers of gene expression. Transcriptional correlates of disorder-related neuroimaging phenotypes are also linked to transcriptionally dysregulated genes identified in ex vivo analyses of patient brains. Modeling studies demonstrate that spatial patterns of gene expression are involved in regional vulnerability to neurodegeneration and the spread of disease across the brain. This growing body of work supports the utility of transcriptional atlases in testing hypotheses about the molecular mechanism driving disease-related changes in macroscopic neuroimaging phenotypes.

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.

Mislocalization of Nucleocytoplasmic Transport Proteins in Human Huntington's Disease PSC-Derived Striatal Neurons

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by a CAG repeat expansion in the huntingtin gene (HTT). Disease progression is characterized by the loss of vulnerable neuronal populations within the striatum. A consistent phenotype across HD models is disruption of nucleocytoplasmic transport and nuclear pore complex (NPC) function. Here we demonstrate that high content imaging is a suitable method for detecting mislocalization of lamin-B1, RAN and RANGAP1 in striatal neuronal cultures thus allowing a robust, unbiased, highly powered approach to assay nuclear pore deficits. Furthermore, nuclear pore deficits extended to the selectively vulnerable DARPP32 + subpopulation neurons, but not to astrocytes. Striatal neuron cultures are further affected by changes in gene and protein expression of RAN, RANGAP1 and lamin-B1. Lowering total HTT using HTT-targeted anti-sense oligonucleotides partially restored gene expression, as well as subtly reducing mislocalization of proteins involved in nucleocytoplasmic transport. This suggests that mislocalization of RAN, RANGAP1 and lamin-B1 cannot be normalized by simply reducing expression of CAG-expanded HTT in the absence of healthy HTT protein.

Planning deficits in Huntington's disease: A brain structural correlation by voxel-based morphometry

Introduction

Early Huntington’s disease (HD) patients begin to show planning deficits even before motor alterations start to manifest. Generally, planning ability is associated with the functioning of anterior brain areas such as the medial prefrontal cortex. However, early HD neuropathology involves significant atrophy in the occipital and parietal cortex, suggesting that more posterior regions could also be involved in these planning deficits.

Objective

To identify brain regions associated with planning deficits in HD patients at an early clinical stage.

Materials and methods

Twenty-two HD-subjects genetically confirmed with incipient clinical manifestation and twenty healthy subjects were recruited. All participants underwent MRI T1 image acquisition as well as testing in the Stockings of Cambridge (SOC) task to measure planning ability. First, group comparison of SOC measures were performed. Then, correlation voxel-based morphometry analyses were done between gray matter degeneration and SOC performance in the HD group.

Results

Accuracy and efficiency planning scores correlated with gray matter density in right lingual gyrus, middle temporal gyrus, anterior cingulate gyrus, and paracingulate gyrus.

Conclusions

Our results suggest that planning deficits exhibited by early HD-subjects are related to occipital and temporal cortical degeneration in addition to the frontal areas deterioration.