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While there is no known cure for Huntington's disease (HD), there are early-phase clinical trials aimed at altering disease progression patterns. There is, however, no obvious single outcome for these trials to evaluate treatment efficacy. Currently used outcomes are, while reasonable, not optimal in any sense. In this paper we derive a method for constructing a composite variable via a linear combination of clinical measures. Our composite variable optimizes the signal-to-noise ratio (SNR) within the context of a longitudinal study design. We also demonstrate how to induce sparsity using a soft-approximation of an L 1 penalty on the coefficients of the composite variable. We applied our method to data from the TRACK-HD study, a longitudinal study aimed at establishing good outcome measures for HD, and found that compared to the existing composite measurement our composite variable provides a larger SNR and allows clinical trials with smaller sample sizes to achieve equivalent power. [ABSTRACT FROM AUTHOR]

Objective: The identification of sensitive biomarkers is essential to validate therapeutics for Huntington disease (HD). We directly compare structural imaging markers across the largest collective imaging HD dataset to identify a set of imaging markers robust to multicenter variation and to derive upper estimates on sample sizes for clinical trials in HD.Methods: We used 1 postprocessing pipeline to retrospectively analyze T1-weighted magnetic resonance imaging (MRI) scans from 624 participants at 3 time points, from the PREDICT-HD, TRACK-HD, and IMAGE-HD studies. We used mixed effects models to adjust regional brain volumes for covariates, calculate effect sizes, and simulate possible treatment effects in disease-affected anatomical regions. We used our model to estimate the statistical power of possible treatment effects for anatomical regions and clinical markers.Results: We identified a set of common anatomical regions that have similarly large standardized effect sizes (>0.5) between healthy control and premanifest HD (PreHD) groups. These included subcortical, white matter, and cortical regions and nonventricular cerebrospinal fluid (CSF). We also observed a consistent spatial distribution of effect size by region across the whole brain. We found that multicenter studies were necessary to capture treatment effect variance; for a 20% treatment effect, power of >80% was achieved for the caudate (n = 661), pallidum (n = 687), and nonventricular CSF (n = 939), and, crucially, these imaging markers provided greater power than standard clinical markers.Interpretation: Our findings provide the first cross-study validation of structural imaging markers in HD, supporting the use of these measurements as endpoints for both observational studies and clinical trials. ANN NEUROL 2020;87:751-762. [ABSTRACT FROM AUTHOR]

Huntington's disease (HD) is a neurodegenerative disorder caused by an abnormal repetition of the cytosine-adenine-guanine (CAG) trinucleotide in the HTT gene. This polyglutamine mutation causes behavioral, cognitive, and motor abnormalities such as chorea. Additionally, HD is characterized by striatal atrophy prior to symptom onset. This experiment investigated gender contributions in pre-diagnosed or prodromal HD stages as well as striatal effect on motor dysfunction. All prodromal HD participants were positive for the genetic mutation. This crosssectional study correlated striatal volume between men and women at different stages of prodromal HD. It was expected to see greater gender differences with increasing prodromal HD stages due to past HD gender studies. Structural Magnetic Resonance (sMRI) data were collected from more than a thousand cans and decomposed into specific regions via independent component analysis. Regions within the striatum became gray matter profiles of interest. Statistical analyses were conducted to quantify a relationship between gender and stage as well as striatal effect on motor dysfunction. Gender did not correlate with striatal volume at different prodromal stages yet striatal volume correlated with motor abnormalities as expected. Additionally, striatal volume decreased with increasing prHD stages. The results supported previous findings associating striatal volume and prHD stages, yet gender contributions were not identified. A study limitation is the use of a cross sectional analysis; interactions between gender and rate of striatal atrophy have yet to be studied longitudinally in a prodromal HD cohort. Indexing prodromal progression factors could enhance therapeutic targets by isolating the earliest-affected regions of the brain in both sexes, which is vital for future treatment. [ABSTRACT FROM AUTHOR]

Objectives: Apathy is a debilitating symptom of Huntington's disease (HD) and manifests before motor diagnosis, making it an excellent therapeutic target in the preclinical phase of Huntington's disease (prHD). HD is a neurological genetic disorder characterized by cognitive and motor impairment, and psychiatric abnormalities. Apathy is not well characterized within the prHD. In previous literature, damage to the caudate and putamen has been correlated with increased apathy in other neurodegenerative and movement disorders. The objective of this study was to determine whether apathy severity in individuals with prHD is related to striatum volumes and cognitive control. We hypothesized that, within prHD individuals, striatum volumes and cognitive control scores would be related to apathy. Methods: We constructed linear mixed models to analyze striatum volumes and cognitive control, a composite measure that includes tasks assessing with apathy scores from 797 prHD participants. The outcome variable for each model was apathy, and the independent variables for the four separate models were caudate volume, putamen volume, cognitive control score, and motor symptom score. We also included depression as a covariate to ensure that our results were not solely related to mood. Results: Caudate and putamen volumes, as well as measures of cognitive control, were significantly related to apathy scores even after controlling for depression. Conclusions: The behavioral apathy expressed by these individuals was related to regions of the brain commonly associated with isolated apathy, and not a direct result of mood symptoms. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Huntington's disease (HD) involves preferential and progressive degeneration of striatum and other subcortical regions as well as regional cortical atrophy. It is caused by a CAG repeat expansion in the Huntingtin gene, and the longer the expansion the earlier the age of onset. Atrophy begins prior to manifest clinical signs and symptoms, and brain atrophy in premanifest expansion carriers can be studied. We employed a diffeomorphometric pipeline to contrast subcortical structures' morphological properties in a control group with three disease groups representing different phases of premanifest HD (far, intermediate, and near to onset) as defined by the length of the CAG expansion and the participant's age (CAG‐Age‐Product). A total of 1,428 magnetic resonance image scans from 694 participants from the PREDICT‐HD cohort were used. We found significant region‐specific atrophies in all subcortical structures studied, with the estimated abnormality onset time varying from structure to structure. Heterogeneous shape abnormalities of caudate nuclei were present in premanifest HD participants estimated furthest from onset and putaminal shape abnormalities were present in participants intermediate to onset. Thalamic, hippocampal, and amygdalar shape abnormalities were present in participants nearest to onset. We assessed whether the estimated progression of subcortical pathology in premanifest HD tracked specific pathways. This is plausible for changes in basal ganglia circuits but probably not for changes in hippocampus and amygdala. The regional shape analyses conducted in this study provide useful insights into the effects of HD pathology in subcortical structures. [ABSTRACT FROM AUTHOR]

Background: Clinician-rated measures of functioning are often used as primary endpoints in clinical trials and other behavioral research in Huntington disease. As study costs for clinician-rated assessments are not always feasible, there is a question of whether patient self-report of commonly used clinician-rated measures may serve as acceptable alternatives in low risk behavioral trials.Aim: The purpose of this paper was to determine the level of agreement between self-report and clinician-ratings of commonly used functional assessment measures in Huntington disease.Design: 486 participants with premanifest or manifest Huntington disease were examined. Total Functional Capacity, Functional Assessment, and Independence Scale assessments from the Unified Huntington Disease Rating scale were completed by clinicians; a self-report version was also completed by individuals with Huntington disease. Cronbach’s α was used to examine internal consistency, one-way analysis of variance was used to examine group differences, and paired t tests, kappa agreement coefficients, and intra-class correlations were calculated to determine agreement between raters.Results: Internal consistency for self-reported ratings of functional capacity and ability were good. There were significant differences between those with premanifest, early-, and late-stage disease; those with later-stage disease reported less ability and independence than the other clinical groups. Although self-report ratings were not a perfect match with associated clinician-rated measures, differences were small. Cutoffs for achieving specified levels of agreement are provided.Conclusions: Depending on the acceptable margin of error in a study, self-reported administration of these functional assessments may be appropriate when clinician-related assessments are not feasible. [ABSTRACT FROM AUTHOR]

In this paper, we present a fully-automated subcortical and ventricular shape generation pipeline that acts on structural magnetic resonance images (MRIs) of the human brain. Principally, the proposed pipeline consists of three steps: (1) automated structure segmentation using the diffeomorphic multi-atlas likelihood-fusion algorithm; (2) study-specific shape template creation based on the Delaunay triangulation; (3) deformation-based shape filtering using the large deformation diffeomorphic metric mapping for surfaces. The proposed pipeline is shown to provide high accuracy, sufficient smoothness, and accurate anatomical topology. Two datasets focused upon Huntington's disease (HD) were used for evaluating the performance of the proposed pipeline. The first of these contains a total of 16 MRI scans, each with a gold standard available, on which the proposed pipeline's outputs were observed to be highly accurate and smooth when compared with the gold standard. Visual examinations and outlier analyses on the second dataset, which contains a total of 1,445 MRI scans, revealed 100% success rates for the putamen, the thalamus, the globus pallidus, the amygdala, and the lateral ventricle in both hemispheres and rates no smaller than 97% for the bilateral hippocampus and caudate. Another independent dataset, consisting of 15 atlas images and 20 testing images, was also used to quantitatively evaluate the proposed pipeline, with high accuracy having been obtained. In short, the proposed pipeline is herein demonstrated to be effective, both quantitatively and qualitatively, using a large collection of MRI scans. [ABSTRACT FROM AUTHOR]