Natural variation in sensory-motor white matter organization influences manifestations of Huntington's disease

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.

Abnormal molecular signatures of inflammation, energy metabolism, and vesicle biology in human Huntington disease peripheral tissues

BACKGROUND

A major challenge in neurodegenerative diseases concerns identifying biological disease signatures that track with disease progression or respond to an intervention. Several clinical trials in Huntington disease (HD), an inherited, progressive neurodegenerative disease, are currently ongoing. Therefore, we examine whether peripheral tissues can serve as a source of readily accessible biological signatures at the RNA and protein level in HD patients.

RESULTS

We generate large, high-quality human datasets from skeletal muscle, skin and adipose tissue to probe molecular changes in human premanifest and early manifest HD patients-those most likely involved in clinical trials. The analysis of the transcriptomics and proteomics data shows robust, stage-dependent dysregulation. Gene ontology analysis confirms the involvement of inflammation and energy metabolism in peripheral HD pathogenesis. Furthermore, we observe changes in the homeostasis of extracellular vesicles, where we find consistent changes of genes and proteins involved in this process. In-depth single nucleotide polymorphism data across the HTT gene are derived from the generated primary cell lines.

CONCLUSIONS

Our 'omics data document the involvement of inflammation, energy metabolism, and extracellular vesicle homeostasis. This demonstrates the potential to identify biological signatures from peripheral tissues in HD suitable as biomarkers in clinical trials. The generated data, complemented by the primary cell lines established from peripheral tissues, and a large panel of iPSC lines that can serve as human models of HD are a valuable and unique resource to advance the current understanding of molecular mechanisms driving HD pathogenesis.

Diagnostic contribution and therapeutic perspectives of transcranial magnetic stimulation in dementia

Transcranial magnetic stimulation (TMS) is a powerful tool to probe in vivo brain circuits, as it allows to assess several cortical properties such asexcitability, plasticity and connectivity in humans. In the last 20 years, TMS has been applied to patients with dementia, enabling the identification of potential markers of thepathophysiology and predictors of cognitive decline; moreover, applied repetitively, TMS holds promise as a potential therapeutic intervention. The objective of this paper is to present a comprehensive review of studies that have employed TMS in dementia and to discuss potential clinical applications, from the diagnosis to the treatment. To provide a technical and theoretical framework, we first present an overview of the basic physiological mechanisms of the application of TMS to assess cortical excitability, excitation and inhibition balance, mechanisms of plasticity and cortico-cortical connectivity in the human brain. We then review the insights gained by TMS techniques into the pathophysiology and predictors of progression and response to treatment in dementias, including Alzheimer's disease (AD)-related dementias and secondary dementias. We show that while a single TMS measure offers low specificity, the use of a panel of measures and/or neurophysiological index can support the clinical diagnosis and predict progression. In the last part of the article, we discuss the therapeutic uses of TMS. So far, only repetitive TMS (rTMS) over the left dorsolateral prefrontal cortex and multisite rTMS associated with cognitive training have been shown to be, respectively, possibly (Level C of evidence) and probably (Level B of evidence) effective to improve cognition, apathy, memory, and language in AD patients, especially at a mild/early stage of the disease. The clinical use of this type of treatment warrants the combination of brain imaging techniques and/or electrophysiological tools to elucidate neurobiological effects of neurostimulation and to optimally tailor rTMS treatment protocols in individual patients or specific patient subgroups with dementia or mild cognitive impairment.

Diffusion imaging in Huntington's disease: comprehensive review

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

Longitudinal 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.

Characterizing White Matter in Huntington's Disease

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

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

Huntington's disease: Brain imaging in Huntington's disease

Huntington's disease (HD) gene-carriers show prominent neuronal loss by end-stage disease, and the use of magnetic resonance imaging (MRI) has been increasingly used to quantify brain changes during earlier stages of the disease. MRI offers an in vivo method of measuring structural and functional brain change. The images collected via MRI are processed to measure different anatomical features, such as brain volume, macro- and microstructural changes within white matter and functional brain activity. Structural imaging has demonstrated significant volume loss across multiple white and gray matter regions in HD, particularly within subcortical structures. There also appears to be increasing disorganization of white matter tracts and between-region connectivity with increasing disease progression. Finally, functional changes are thought to represent changes in brain activity underlying compensatory mechanisms in HD. This chapter will provide an overview of the principles of MRI and practicalities associated with using MRI in HD studies, and summarize findings from MRI studies investigating brain structure and function in HD.

Concurrent Cross-Sectional and Longitudinal Analyses of Multivariate White Matter Profiles and Clinical Functioning in Pre-Diagnosis Huntington Disease

BACKGROUND

Gray matter (GM) atrophy in the striatum and across the brain is a consistently reported feature of the Huntington Disease (HD) prodrome. More recently, widespread prodromal white matter (WM) degradation has also been detected. However, longitudinal WM studies are limited and conflicting, and most analyses comparing WM and clinical functioning have also been cross-sectional.

OBJECTIVE

We simultaneously assessed changes in WM and cognitive and motor functioning at various prodromal HD stages.

METHODS

Data from 1,336 (1,047 prodromal, 289 control) PREDICT-HD participants were analyzed (3,700 sessions). MRI images were used to create GM, WM, and cerebrospinal fluid probability maps. Using source-based morphometry, independent component analysis was applied to WM probability maps to extract covarying spatial patterns and their subject profiles. WM profiles were analyzed in two sets of linear mixed model (LMM) analyses: one to compare WM profiles across groups cross-sectionally and longitudinally, and one to concurrently compare WM profiles and clinical variables cross-sectionally and longitudinally within each group.

RESULTS

Findings illustrate widespread prodromal changes in GM-adjacent-WM, with premotor, supplementary motor, middle frontal and striatal changes early in the prodrome that subsequently extend sub-gyrally with progression. Motor functioning agreed most with WM until the near-onset prodromal stage, when Stroop interference was the best WM indicator. Across groups, Trail-Making Test part A outperformed other cognitive variables in its similarity to WM, particularly cross-sectionally.

CONCLUSIONS

Results suggest that distinct regions coincide with cognitive compared to motor functioning. Furthermore, at different prodromal stages, distinct regions appear to align best with clinical functioning. Thus, the informativeness of clinical measures may vary according to the type of data available (cross-sectional or longitudinal) as well as age and CAG-number.

Multiple clinical features of Huntington's disease correlate with mutant HTT gene CAG repeat lengths and neurodegeneration

Huntington's disease (HD) is a fatal neurodegenerative disease caused by mutant HTT gene expansions of CAG triplet repeat numbers that are inherited in an autosomal dominant manner. HD patients display multiple clinical features that are correlated with HTT CAG repeat numbers that include age of disease onset, motor dysfunction, cognitive deficits, compromised daily living capacity, and brain neurodegeneration. It is important to understand the significant relationships of the multiple HD clinical deficits correlated with the number of mutant HTT CAG expansions that are the genetic basis for HD disabilities. Therefore, this review highlights the significant correlations of the HD clinical features of age of onset, motor and cognitive disabilities, decline in living capabilities, weight loss, risk of death, and brain neurodegeneration with respect to their associations with CAG repeat lengths of the HTT gene. Quantitative HTT gene expression patterns analyzed in normal adult human brain regions demonstrated its distribution in areas known to undergo neurodegeneration in HD, as well as in other brain regions. Future investigation of the relationships of the spectrum of clinical HD features with mutant HTT molecular mechanisms will be important to gain understanding of how mutant CAG expansions of the HTT gene result in the devastating disabilities of HD patients.

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

Huntington's disease (HD) is a monogenic neurodegenerative disorder caused by a CAG‐repeat expansion in the Huntingtin gene. Presence of this expansion signifies certainty of disease onset, but only partly explains age at which onset occurs. Genome‐wide association studies have shown that naturally occurring genetic variability influences HD pathogenesis and disease onset. Investigating the influence of biological traits in the normal population, such as variability in white matter properties, on HD pathogenesis could provide a complementary approach to understanding disease modification. We have previously shown that while white matter diffusivity patterns in the left sensorimotor network were similar in controls and HD gene‐carriers, they were more extreme in the HD group. We hypothesized that the influence of natural variation in diffusivity on effects of HD pathogenesis on white matter is not limited to the sensorimotor network but extends to cognitive, limbic, and visual networks. Using tractography, we investigated 32 bilateral pathways within HD‐related networks, including motor, cognitive, and limbic, and examined diffusivity metrics using principal components analysis. We identified three independent patterns of diffusivity common to controls and HD gene‐carriers that predicted HD status. The first pattern involved almost all tracts, the second was limited to sensorimotor tracts, and the third encompassed cognitive network tracts. Each diffusivity pattern was associated with network specific performance. The consistency in diffusivity patterns across both groups coupled with their association with disease status and task performance indicates that naturally‐occurring patterns of diffusivity can become accentuated in the presence of the HD gene mutation to influence clinical brain function.

Motor cortex synchronization influences the rhythm of motor performance in premanifest huntington's disease

BACKGROUND

In Huntington's disease there is evidence of structural damage in the motor system, but it is still unclear how to link this to the behavioral disorder of movement. One feature of choreic movement is variable timing and coordination between sequences of actions. We postulate this results from desynchronization of neural activity in cortical motor areas.

OBJECTIVES

The objective of this study was to explore the ability to synchronize activity in a motor network using transcranial magnetic stimulation and to relate this to timing of motor performance.

METHODS

We examined synchronization in oscillatory activity of cortical motor areas in response to an external input produced by a pulse of transcranial magnetic stimulation. We combined this with EEG to compare the response of 16 presymptomatic Huntington's disease participants with 16 age-matched healthy volunteers to test whether the strength of synchronization relates to the variability of motor performance at the following 2 tasks: a grip force task and a speeded-tapping task.

RESULTS

Phase synchronization in response to M1 stimulation was lower in Huntington's disease than healthy volunteers (P < .01), resulting in a reduced cortical activity at global (P < .02) and local levels (P < .01). Participants who showed better timed motor performance also showed stronger oscillatory synchronization (r = -0.356; P < .05) and higher cortical activity (r = -0.393; P < .05).

CONCLUSIONS

Our data may model the ability of the motor command to respond to more subtle, physiological inputs from other brain areas. This novel insight indicates that impairments of the timing accuracy of synchronization and desynchronization could be a physiological basis for some key clinical features of Huntington's disease. © 2018 International Parkinson and Movement Disorder Society.

Magnetic Resonance Imaging in Huntington's Disease

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

The reliability of commonly used electrophysiology measures

BACKGROUND

Electrophysiological measures can help understand brain function both in healthy individuals and in the context of a disease. Given the amount of information that can be extracted from these measures and their frequent use, it is essential to know more about their inherent reliability.

OBJECTIVE/HYPOTHESIS

To understand the reliability of electrophysiology measures in healthy individuals. We hypothesized that measures of threshold and latency would be the most reliable and least susceptible to methodological differences between study sites.

METHODS

Somatosensory evoked potentials from 112 control participants; long-latency reflexes, transcranial magnetic stimulation with resting and active motor thresholds, motor evoked potential latencies, input/output curves, and short-latency sensory afferent inhibition and facilitation from 84 controls were collected at 3 visits over 24 months at 4 Track-On HD study sites. Reliability was assessed using intra-class correlation coefficients for absolute agreement, and the effects of reliability on statistical power are demonstrated for different sample sizes and study designs.

RESULTS

Measures quantifying latencies, thresholds, and evoked responses at high stimulator intensities had the highest reliability, and required the smallest sample sizes to adequately power a study. Very few between-site differences were detected.

CONCLUSIONS

Reliability and susceptibility to between-site differences should be evaluated for electrophysiological measures before including them in study designs. Levels of reliability vary substantially across electrophysiological measures, though there are few between-site differences. To address this, reliability should be used in conjunction with theoretical calculations to inform sample size and ensure studies are adequately powered to detect true change in measures of interest.

Neuroimaging as a tool to study the sources of phenotypic heterogeneity in Huntington's disease

PURPOSE OF REVIEW

Huntington's disease is a neurodegenerative disorder characterized by a triad of motor, cognitive and psychiatric disturbances. There is great variability regarding the prominence and evolution of each type of clinical sign. One possible source of phenotypic heterogeneity could be the more prominent degeneration of specific brain circuits. The scope of this review is to highlight the most recent neuroimaging studies that have analysed the relationship between brain changes and motor, cognitive and psychiatric alterations in Huntington's disease.

RECENT FINDINGS

The results from recent neuroimaging studies are heterogeneous. Although there is a great overlap between the different regions associated with each symptomatic domain, there is some degree of differentiation. For example, the motor network is associated with motor impairment, whereas the ventral striatum is especially involved in emotional deficits related with psychiatric problems.

SUMMARY

Motor, cognitive and psychiatric impairments are associated with structural and functional brain biomarkers. However, the specificity of the regions involved remains unknown, because these studies focused on specific regions and symptoms. In order to tease apart the neural substrates that underlie the phenotypic heterogeneity in Huntington's disease, multivariate approaches combining brain and behavioural measures related to all symptomatic domains should be considered in the future.