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

Modifiable factors associated with Huntington's disease progression in presymptomatic participants

OBJECTIVE

Huntington's disease (HD) is a neurodegenerative disorder characterized by progressive motor, cognitive, and psychiatric symptoms. Our aim here was to identify factors that can be modified to slow disease progression even before the first symptoms appear.

METHODS

We included 2636 presymptomatic individuals (comparison with family controls) drawn from the prospective observational cohort Enroll-HD, with more than 35 CAG repeats and at least two assessments of disease progression measured with the composite Huntington's disease rating Scale (cUHDRS). The association between sociodemographic factors, health behaviors, health history, and cUHDRS trajectory was assessed with a mixed-effects random forest using partial dependence plots and Shapley additive explanation method.

RESULTS

Participants were followed by an average of 3.4 (SD = 1.97) years. We confirmed the negative impact of age and a high number of CAG repeats. We found that a high level of education, a body mass index (BMI) <23 kg/m2 before the age of 40 and >23 kg/m2 thereafter, alcohol consumption of <15 units per week, current coffee consumption and no smoking were linked to slow disease progression, as did no previous exposure to antidepressants or anxiolytic, no psychiatric history or comorbidities, and being female. Other comorbidities or marital status showed no major association with HD evolution.

INTERPRETATION

Reducing modifiable risk factors for HD is one way to support the presymptomatic population. A high level of education, low-to-moderate alcohol consumption, no smoking, and BMI control are likely to slow disease progression in this population.

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.

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.

Alterations in Cerebrospinal Fluid Urea Occur in Late Manifest Huntington's Disease

Background

Huntington's disease (HD) is a neurodegenerative disorder caused by expanded cytosine-adenine-guanine (CAG) repeats in the Huntingtin gene, resulting in the production of mutant huntingtin proteins (mHTT). Previous research has identified urea as a key metabolite elevated in HD animal models and postmortem tissues of HD patients. However, the relationship between disease course and urea elevations, along with the molecular mechanisms responsible for these disturbances remain unknown.

Objective

To better understand the molecular disturbances and timing of urea cycle metabolism across different stages in HD.

Methods

We completed a global metabolomic profile of cerebrospinal fluid (CSF) from individuals who were at several stages of disease: pre-manifest (PRE), manifest (MAN), and late manifest (LATE) HD participants, and compared to controls.

Results

Approximately 500 metabolites were significantly altered in PRE participants compared to controls, although no significant differences in CSF urea or urea metabolites were observed. CSF urea was significantly elevated in LATE participants only. There were no changes in the urea metabolites citrulline, ornithine, and arginine.

Conclusions

Overall, our study confirms that CSF elevations occur late in the HD course, and these changes may reflect accumulating deficits in cellular energy metabolism.

Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group

 Neuroimaging is increasingly being included in clinical trials of Huntington's disease (HD) for a wide range of purposes from participant selection and safety monitoring, through to demonstration of disease modification. Selection of the appropriate modality and associated analysis tools requires careful consideration. On behalf of the EHDN Imaging Working Group, we present current opinion on the utility and future prospects for inclusion of neuroimaging in HD trials. Covering the key imaging modalities of structural-, functional- and diffusion- MRI, perfusion imaging, positron emission tomography, magnetic resonance spectroscopy, and magnetoencephalography, we address how neuroimaging can be used in HD trials to: 1) Aid patient selection, enrichment, stratification, and safety monitoring; 2) Demonstrate biodistribution, target engagement, and pharmacodynamics; 3) Provide evidence for disease modification; and 4) Understand brain re-organization following therapy. We also present the challenges of translating research methodology into clinical trial settings, including equipment requirements and cost, standardization of acquisition and analysis, patient burden and invasiveness, and interpretation of results. We conclude, that with appropriate consideration of modality, study design and analysis, imaging has huge potential to facilitate effective clinical trials in HD.

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.

Progressive alterations in white matter microstructure across the timecourse of Huntington's disease

BACKGROUND

Whole-brain longitudinal diffusion studies are crucial to examine changes in structural connectivity in neurodegeneration. Here, we investigated the longitudinal alterations in white matter (WM) microstructure across the timecourse of Huntington's disease (HD).

METHODS

We examined changes in WM microstructure from premanifest to early manifest disease, using data from two cohorts with different disease burden. The TrackOn-HD study included 67 controls, 67 premanifest, and 10 early manifest HD (baseline and 24-month data); the PADDINGTON study included 33 controls and 49 early manifest HD (baseline and 15-month data). Longitudinal changes in fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity, and radial diffusivity from baseline to last study visit were investigated for each cohort using tract-based spatial statistics. An optimized pipeline was employed to generate participant-specific templates to which diffusion tensor imaging maps were registered and change maps were calculated. We examined longitudinal differences between HD expansion-carriers and controls, and correlations with clinical scores, including the composite UHDRS (cUHDRS).

RESULTS

HD expansion-carriers from TrackOn-HD, with lower disease burden, showed a significant longitudinal decline in FA in the left superior longitudinal fasciculus and an increase in MD across subcortical WM tracts compared to controls, while in manifest HD participants from PADDINGTON, there were significant widespread longitudinal increases in diffusivity compared to controls. Baseline scores in clinical scales including the cUHDRS predicted WM microstructural change in HD expansion-carriers.

CONCLUSION

The present study showed significant longitudinal changes in WM microstructure across the HD timecourse. Changes were evident in larger WM areas and across more metrics as the disease advanced, suggesting a progressive alteration of WM microstructure with disease evolution.

Subtyping monogenic disorders: Huntington disease

Huntington disease is a highly disabling neurodegenerative disease characterized by psychiatric, cognitive, and motor deficits. The causal genetic mutation in huntingtin (Htt, also known as IT15), located on chromosome 4p16.3, leads to an expansion of a triplet coding for polyglutamine. The expansion is invariably associated with the disease when >39 repeats. Htt encodes for the protein huntingtin (HTT), which carries out many essential biological functions in the cell, in particular in the nervous system. The precise mechanism of toxicity is not known. Based on a one-gene-one-disease framework, the prevailing hypothesis ascribes toxicity to the universal aggregation of HTT. However, the aggregation process into mutant huntingtin (mHTT) is associated with a reduction of the levels of wild-type HTT. A loss of wild-type HTT may plausibly be pathogenic, contributing to the disease onset and progressive neurodegeneration. Moreover, many other biological pathways are altered in Huntington disease, such as in the autophagic system, mitochondria, and essential proteins beyond HTT, potentially explaining biological and clinical differences among affected individuals. As one gene does not mean one disease, future efforts at identifying specific Huntington subtypes are important to design biologically tailored therapeutic approaches that correct the corresponding biological pathways-rather than continuing to exclusively target the common denominator of HTT aggregation for elimination.

Brain Alterations in Aged OVT73 Sheep Model of Huntington's Disease: An MRI Based Approach

BACKGROUND

Huntington's disease (HD) is a fatal neurodegenerative autosomal dominant disorder with prevalence of 1 : 20000 that has no effective treatment to date. Translatability of candidate therapeutics could be enhanced by additional testing in large animal models because of similarities in brain anatomy, size, and immunophysiology. These features enable realistic pre-clinical studies of biodistribution, efficacy, and toxicity.

OBJECTIVE AND METHODS

Here we non-invasively characterized alterations in brain white matter microstructure, neurochemistry, neurological status, and mutant Huntingtin protein (mHTT) levels in cerebrospinal fluid (CSF) of aged OVT73 HD sheep.

RESULTS

Similar to HD patients, CSF mHTT differentiates HD from normal sheep. Our results are indicative of a decline in neurological status, and alterations in brain white matter diffusion and spectroscopy metric that are more severe in aged female HD sheep. Longitudinal analysis of aged female HD sheep suggests that the decline is detectable over the course of a year. In line with reports of HD human studies, white matter alterations in corpus callosum correlates with a decline in gait of HD sheep. Moreover, alterations in the occipital cortex white matter correlates with a decline in clinical rating score. In addition, the marker of energy metabolism in striatum of aged HD sheep, shows a correlation with decline of clinical rating score and eye coordination.

CONCLUSION

This data suggests that OVT73 HD sheep can serve as a pre-manifest large animal model of HD providing a platform for pre-clinical testing of HD therapeutics and non-invasive tracking of the efficacy of the therapy.

Interaction between sex and neurofilament light chain on brain structure and clinical severity in Huntington's disease

Female Huntington’s disease (HD) patients have consistently shown a faster clinical worsening than male, but the underlying mechanisms responsible for this observation remain unknown. Here, we describe how sex modifies the impact of neurodegeneration on brain atrophy and clinical severity in HD. Cerebrospinal fluid neurofilament light chain (NfL) levels were used as a biological measure of neurodegeneration, and brain atrophy was assessed by structural magnetic resonance imaging. We found that larger NfL values in women reflect higher brain atrophy and clinical severity than in men (p < 0.05 for an interaction model). This differential vulnerability could have important implications in clinical trials.

Neuroimaging, Urinary, and Plasma Biomarkers of Treatment Response in Huntington's Disease: Preclinical Evidence with the p75NTR Ligand LM11A-31

Huntington's disease (HD) is caused by an expansion of the CAG repeat in the huntingtin gene leading to preferential neurodegeneration of the striatum. Disease-modifying treatments are not yet available to HD patients and their development would be facilitated by translatable pharmacodynamic biomarkers. Multi-modal magnetic resonance imaging (MRI) and plasma cytokines have been suggested as disease onset/progression biomarkers, but their ability to detect treatment efficacy is understudied. This study used the R6/2 mouse model of HD to assess if structural neuroimaging and biofluid assays can detect treatment response using as a prototype the small molecule p75NTR ligand LM11A-31, shown previously to reduce HD phenotypes in these mice. LM11A-31 alleviated volume reductions in multiple brain regions, including striatum, of vehicle-treated R6/2 mice relative to wild-types (WTs), as assessed with in vivo MRI. LM11A-31 also normalized changes in diffusion tensor imaging (DTI) metrics and diminished increases in certain plasma cytokine levels, including tumor necrosis factor-alpha and interleukin-6, in R6/2 mice. Finally, R6/2-vehicle mice had increased urinary levels of the p75NTR extracellular domain (ecd), a cleavage product released with pro-apoptotic ligand binding that detects the progression of other neurodegenerative diseases; LM11A-31 reduced this increase. These results are the first to show that urinary p75NTR-ecd levels are elevated in an HD mouse model and can be used to detect therapeutic effects. These data also indicate that multi-modal MRI and plasma cytokine levels may be effective pharmacodynamic biomarkers and that using combinations of these markers would be a viable and powerful option for clinical trials.