Longitudinal imaging highlights preferential basal ganglia circuit atrophy in Huntington's disease

Huntington's disease is caused by a CAG repeat expansion in the Huntingtin gene (HTT), coding for polyglutamine in the Huntingtin protein, with longer CAG repeats causing earlier age of onset. The variable 'Age' × ('CAG'-L), where 'Age' is the current age of the individual, 'CAG' is the repeat length and L is a constant (reflecting an approximation of the threshold), termed the 'CAG Age Product' (CAP) enables the consideration of many individuals with different CAG repeat expansions at the same time for analysis of any variable and graphing using the CAG Age Product score as the X axis. Structural MRI studies have showed that progressive striatal atrophy begins many years prior to the onset of diagnosable motor Huntington's disease, confirmed by longitudinal multicentre studies on three continents, including PREDICT-HD, TRACK-HD and IMAGE-HD. However, previous studies have not clarified the relationship between striatal atrophy, atrophy of other basal ganglia structures, and atrophy of other brain regions. The present study has analysed all three longitudinal datasets together using a single image segmentation algorithm and combining data from a large number of subjects across a range of CAG Age Product score. In addition, we have used a strategy of normalizing regional atrophy to atrophy of the whole brain, in order to determine which regions may undergo preferential degeneration. This made possible the detailed characterization of regional brain atrophy in relation to CAG Age Product score. There is dramatic selective atrophy of regions involved in the basal ganglia circuit-caudate, putamen, nucleus accumbens, globus pallidus and substantia nigra. Most other regions of the brain appear to have slower but steady degeneration. These results support (but certainly do not prove) the hypothesis of circuit-based spread of pathology in Huntington's disease, possibly due to spread of mutant Htt protein, though other connection-based mechanisms are possible. Therapeutic targets related to prion-like spread of pathology or other mechanisms may be suggested. In addition, they have implications for current neurosurgical therapeutic approaches, since delivery of therapeutic agents solely to the caudate and putamen may miss other structures affected early, such as nucleus accumbens and output nuclei of the striatum, the substantia nigra and the globus pallidus.

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.

Death Anxiety in Huntington Disease: Longitudinal Heath-Related Quality-of-Life Outcomes

Objective: Death anxiety, represented by the HDQLIFE™ Concern with Death and Dying (CwDD) patient-reported outcome (PRO) questionnaire, captures a person's worry about the death and dying process. Previous work suggests that death anxiety remains an unremitting burden throughout all stages of Huntington disease (HD). Although palliative interventions have lessened death anxiety among people with advanced cancer, none has yet to undergo testing in the HD population. An account of how death anxiety is associated with longitudinal changes to aspects of health-related quality of life (HRQoL) would help optimize neuropalliative interventions for people with HD. Methods: HDQLIFE collected PROs concerning physical, mental, social, and cognitive HRQoL domains and clinician-rated assessments from people with HD at baseline and 12 and 24 months. Linear mixed-effects models were created to determine how baseline death anxiety was associated with follow-up changes in HRQoL PROs after controlling for baseline death anxiety and other disease and sociodemographic covariates. Results: Higher baseline HDQLIFE CwDD is associated with 12- and 24-month declines in HDQLIFE Speech Difficulties, neurology quality of life (NeuroQoL) Depression, Suicidality, HDQLIFE Meaning and Purpose, and NeuroQoL Positive Affect and Well-being. Interpretation: Death anxiety may be a risk factor for worsening mental health and speech difficulty. A further prospective study is required to evaluate whether interventions on death anxiety or mental health generally can reduce declines in HRQoL for people with HD over time.

Vascular contributions to Alzheimer's disease

Alzheimer's disease (AD) is the most common cause of dementia and is characterized by progressive neurodegeneration and cognitive decline. Understanding the pathophysiology underlying AD is paramount for the management of individuals at risk of and suffering from AD. The vascular hypothesis stipulates a relationship between cardiovascular disease and AD-related changes although the nature of this relationship remains unknown. In this review, we discuss several potential pathological pathways of vascular involvement in AD that have been described including dysregulation of neurovascular coupling, disruption of the blood brain barrier, and reduced clearance of metabolite waste such as beta-amyloid, a toxic peptide considered the hallmark of AD. We will also discuss the two-hit hypothesis which proposes a 2-step positive feedback loop in which microvascular insults precede the accumulation of Aß and are thought to be at the origin of the disease development. At neuroimaging, signs of vascular dysfunction such as chronic cerebral hypoperfusion have been demonstrated, appearing early in AD, even before cognitive decline and alteration of traditional biomarkers. Cerebral small vessel disease such as cerebral amyloid angiopathy, characterized by the aggregation of Aß in the vessel wall, is highly prevalent in vascular dementia and AD patients. Current data is unclear whether cardiovascular disease causes, precipitates, amplifies, precedes, or simply coincides with AD. Targeted imaging tools to quantitatively evaluate the intracranial vasculature and longitudinal studies in individuals at risk for or in the early stages of the AD continuum could be critical in disentangling this complex relationship between vascular disease and AD.

Comprehensive shape analysis of the cortex in Huntington's disease

The striatum has traditionally been the focus of Huntington's disease research due to the primary insult to this region and its central role in motor symptoms. Beyond the striatum, evidence of cortical alterations caused by Huntington's disease has surfaced. However, findings are not coherent between studies which have used cortical thickness for Huntington's disease since it is the well-established cortical metric of interest in other diseases. In this study, we propose a more comprehensive approach to cortical morphology in Huntington's disease using cortical thickness, sulcal depth, and local gyrification index. Our results show consistency with prior findings in cortical thickness, including its limitations. Our comparison between cortical thickness and local gyrification index underscores the complementary nature of these two measures-cortical thickness detects changes in the sensorimotor and posterior areas while local gyrification index identifies insular differences. Since local gyrification index and cortical thickness measures detect changes in different regions, the two used in tandem could provide a clinically relevant measure of disease progression. Our findings suggest that differences in insular regions may correspond to earlier neurodegeneration and may provide a complementary cortical measure for detection of subtle early cortical changes due to Huntington's disease.

Factors Associated with the Place of Death in Huntington Disease: Analysis of Enroll-HD

Background: Most people prefer to die at home. Hospice is the standard in end-of-life care for people with Huntington disease (HD), a neurodegenerative genetic disorder that affects people in middle adulthood. Yet, we have little knowledge regarding the place of death for people with HD. Therefore, the current state of knowledge limits HD clinicians' ability to conduct high-quality goals of care conversations. Objectives: We sought to determine the factors associated with the place of death in people with HD. Design: We obtained cross-sectional data from Enroll-HD and included participants with a positive HD mutation of 36 or more CAG repeats. Results: Out of 16,120 participants in the Enroll-HD study, 536 were reported as deceased. The mean age at death was 60. The leading place of death was home (29%), followed by the hospital (23%). The adjusted odds ratio (aOR) of dying at a skilled nursing facility was significantly lower for those partnered (aOR: 0.48, confidence interval [95% CI]: 0.26-0.86). The aOR for dying on hospice compared to home was increased in a person with some college and above (aOR: 2.40, 95% CI: 1.21-4.75). Conclusions: Our data further suggest that models that predict the place of death for serious illnesses do not appear to generalize to HD. The distribution in the places of death within HD was not uniform. Our findings may assist HD clinicians in communication during goals of care conversations.

Moving beyond disclosure: Stages of care in preclinical Alzheimer's disease biomarker testing

Alzheimer's disease (AD) begins with an asymptomatic "preclinical" phase, in which abnormal biomarkers indicate risk for developing cognitive impairment. Biomarker information is increasingly being disclosed in research settings, and is moving toward clinical settings with the development of cheaper and non-invasive testing. Limited research has focused on the safety and psychological effects of disclosing biomarker results to cognitively unimpaired adults. However, less is known about how to ensure equitable access and robust counseling for decision-making before testing, and how to effectively provide long-term follow-up and risk management after testing. Using the framework of Huntington's disease, which is based on extensive experience with disclosing and managing risk for a progressive neurodegenerative condition, this article proposes a conceptual model of pre-disclosure, disclosure, and post-disclosure phases for AD biomarker testing. Addressing research questions in each phase will facilitate the transition of biomarker testing into clinical practice.

Genetic modifiers of Huntington disease differentially influence motor and cognitive domains

Genome-wide association studies (GWASs) of Huntington disease (HD) have identified six DNA maintenance gene loci (among others) as modifiers and implicated a two step-mechanism of pathogenesis: somatic instability of the causative HTT CAG repeat with subsequent triggering of neuronal damage. The largest studies have been limited to HD individuals with a rater-estimated age at motor onset. To capitalize on the wealth of phenotypic data in several large HD natural history studies, we have performed algorithmic prediction by using common motor and cognitive measures to predict age at other disease landmarks as additional phenotypes for GWASs. Combined with imputation with the Trans-Omics for Precision Medicine reference panel, predictions using integrated measures provided objective landmark phenotypes with greater power to detect most modifier loci. Importantly, substantial differences in the relative modifier signal across loci, highlighted by comparing common modifiers at MSH3 and FAN1, revealed that individual modifier effects can act preferentially in the motor or cognitive domains. Individual components of the DNA maintenance modifier mechanisms may therefore act differentially on the neuronal circuits underlying the corresponding clinical measures. In addition, we identified additional modifier effects at the PMS1 and PMS2 loci and implicated a potential second locus on chromosome 7. These findings indicate that broadened discovery and characterization of HD genetic modifiers based on additional quantitative or qualitative phenotypes offers not only the promise of in-human validated therapeutic targets but also a route to dissecting the mechanisms and cell types involved in both the somatic instability and toxicity components of HD pathogenesis.

Traumatic Brain Injury in Children and Adolescents: Psychiatric Disorders 24 Years Later

OBJECTIVE

The investigators aimed to extend findings regarding predictive factors of psychiatric outcomes among children and adolescents with traumatic brain injury (TBI) from 2 to 24 years postinjury.

METHODS

Youths aged 6-14 years who were hospitalized following TBI from 1992 to 1994 were assessed at baseline for TBI severity and for preinjury psychiatric, adaptive, and behavioral functioning; family functioning; family psychiatric history; socioeconomic status; and intelligence within weeks of injury. Predictors of psychiatric outcomes following pediatric TBI at 3, 6, 12, and 24 months postinjury have previously been reported. In this study, repeat psychiatric assessments were completed at 24 years postinjury with the same cohort, now adults aged 29-39 years, with the outcome measure being presence of a psychiatric disorder not present before the TBI ("novel psychiatric disorder").

RESULTS

Fifty participants with pediatric TBI were initially enrolled, and the long-term outcome analyses focused on data from 45 individuals. Novel psychiatric disorder was present in 24 out of 45 (53%) participants. Presence of a current novel psychiatric disorder was independently predicted by the presence of a preinjury lifetime psychiatric disorder and by severity of TBI.

CONCLUSIONS

Long-term psychiatric outcome (mean=23.92 years [SD=2.17]) in children and adolescents hospitalized for TBI can be predicted at the point of the initial hospitalization encounter by the presence of a preinjury psychiatric disorder and by greater injury severity.

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.

A Multi-Study Model-Based Evaluation of the Sequence of Imaging and Clinical Biomarker Changes in Huntington's Disease

Understanding the order and progression of change in biomarkers of neurodegeneration is essential to detect the effects of pharmacological interventions on these biomarkers. In Huntington’s disease (HD), motor, cognitive and MRI biomarkers are currently used in clinical trials of drug efficacy. Here for the first time we use directly compare data from three large observational studies of HD (total N = 532) using a probabilistic event-based model (EBM) to characterise the order in which motor, cognitive and MRI biomarkers become abnormal. We also investigate the impact of the genetic cause of HD, cytosine-adenine-guanine (CAG) repeat length, on progression through these stages. We find that EBM uncovers a broadly consistent order of events across all three studies; that EBM stage reflects clinical stage; and that EBM stage is related to age and genetic burden. Our findings indicate that measures of subcortical and white matter volume become abnormal prior to clinical and cognitive biomarkers. Importantly, CAG repeat length has a large impact on the timing of onset of each stage and progression through the stages, with a longer repeat length resulting in earlier onset and faster progression. Our results can be used to help design clinical trials of treatments for Huntington’s disease, influencing the choice of biomarkers and the recruitment of participants.

Meaning and purpose in Huntington's disease: a longitudinal study of its impact on quality of life

Objective

Previous work in Huntington’s disease (HD) has shown that a sense of meaning and purpose (M&P) is positively associated with positive affect and well‐being (PAW); however, it was unknown whether HD‐validated patient‐reported outcomes (PROs) influence this association and how M&P impacts PROs in the future. Our study was designed to examine if HD‐validated PROs moderate the relationship between M&P and PAW and to evaluate if baseline M&P predicts 12‐ and 24‐month changes in HD‐validated PROs.

Methods

This was a longitudinal, multicenter study to develop several PROs (e.g., specific for the physical, emotional, cognitive, and social domains) for people with HD (HDQLIFE). The sample consisted of 322 people with HD (n = 50 prodromal, n = 171 early‐stage manifest, and n = 101 late‐stage manifest HD). A single, multivariate linear mixed‐effects model was performed with PAW as the outcome predicted by main effects for M&P and several moderators (i.e., an HD‐validated PRO) and interactions between M&P and a given PRO. Linear‐mixed models were also used to assess if baseline M&P predicted HD‐validated PROs at 12 and 24 months.

Results

Higher M&P was positively associated with higher PAW regardless of the magnitude of symptom burden, as represented by HD‐validated PROs, and independent of disease stage. In our primary analysis, baseline M&P predicted increased PAW and decreased depression, anxiety, anger, emotional/behavioral disruptions, and cognitive decline at 12 and 24 months across all disease stages.

Interpretation

These findings parallel those seen in the oncology population and have implications for adapting and developing psychotherapeutic and palliative HD interventions.

Mild Cognitive Impairment as an Early Landmark in Huntington's Disease

As one of the clinical triad in Huntington's disease (HD), cognitive impairment has not been widely accepted as a disease stage indicator in HD literature. This work aims to study cognitive impairment thoroughly for prodromal HD individuals with the data from a 12-year observational study to determine whether Mild Cognitive Impairment (MCI) in HD gene-mutation carriers is a defensible indicator of early disease. Prodromal HD gene-mutation carriers evaluated annually at one of 32 worldwide sites from September 2002 to April 2014 were evaluated for MCI in six cognitive domains. Linear mixed-effects models were used to determine age-, education-, and retest-adjusted cut-off values in cognitive assessment for MCI, and then the concurrent and predictive validity of MCI was assessed. Accelerated failure time (AFT) models were used to determine the timing of MCI (single-, two-, and multiple-domain), and dementia, which was defined as MCI plus functional loss. Seven hundred and sixty-eight prodromal HD participants had completed all six cognitive tasks, had MRI, and underwent longitudinal assessments. Over half (i.e., 54%) of the participants had MCI at study entry, and half of these had single-domain MCI. Compared to participants with intact cognitive performances, prodromal HD with MCI had higher genetic burden, worsened motor impairment, greater brain atrophy, and a higher likelihood of estimated HD onset. Prospective longitudinal study of those without MCI at baseline showed that 48% had MCI in subsequent visits and data visualization suggested that single-domain MCI, two-domain MCI, and dementia represent appropriate cognitive impairment staging for HD gene-mutation carriers. Findings suggest that MCI represents an early landmark of HD and may be a sensitive enrichment variable or endpoint for prodromal clinical trials of disease modifying therapeutics.

Long-Term Psychiatric Outcomes in Adults with History of Pediatric Traumatic Brain Injury

The objective of the study was to compare psychiatric outcomes in adults with and without history of pediatric traumatic brain injury (TBI). Youth ages 6 to 14 years hospitalized for TBI from 1992 to 1994 were assessed at baseline and at 3, 6, 12, and 24 months post-injury. In the current study, psychiatric assessments were repeated at 24 years post-injury with the same cohort, now adults ages 29 to 39 years. A control group of healthy adults also was recruited for one-time cross-sectional assessments. Outcome measures included: 1) presence of a psychiatric disorder since the 24-month assessment not present before the TBI ("novel psychiatric disorder," NPD), or in the control group, the presence of a psychiatric disorder that developed after the mean age of injury of the TBI group plus 2 years; and 2) Time-to-Event for onset of an NPD during the same time periods. In the TBI group, NPDs were significantly more common, and presence of a current NPD was significantly predicted by presence of a pre-injury lifetime psychiatric disorder and by abnormal day-of-injury computed tomography (CT) scan. Compared with controls, the TBI group also had significantly shorter Time-to-Event for onset of any NPD. These findings demonstrate that long-term psychiatric outcomes in adults previously hospitalized for pediatric TBI are significantly worse when compared with adult controls without history of pediatric TBI, both in terms of prevalence and earlier onset of NPD. Further, in the TBI group, long-term NPD outcome is predicted independently by presence of pre-injury psychiatric disorder and abnormal day-of-injury CT scan.

Tracking Huntington's Disease Progression Using Motor, Functional, Cognitive, and Imaging Markers

BACKGROUND

Potential therapeutic targets and clinical trials for Huntington's disease have grown immensely in the last decade. However, to improve clinical trial outcomes, there is a need to better characterize profiles of signs and symptoms across different epochs of the disease to improve selection of participants.

OBJECTIVE

The objective of the present study was to best distinguish longitudinal trajectories across different Huntington's disease progression groups.

METHODS

Clinical and morphometric imaging data from 1082 participants across IMAGE-HD, TRACK-HD, and PREDICT-HD studies were combined, with longitudinal times ranging between 1 and 10 years. Participants were classified into 4 groups using CAG and age product. Using multivariate linear mixed modeling, 63 combinations of markers were tested for their sensitivity in differentiating CAG and age product groups. Next, multivariate linear mixed modeling was applied to define the best combination of markers to track progression across individual CAG and age product groups.

RESULTS

Putamen and caudate volumes, individually and/or combined, were identified as the best variables to both differentiate CAG and age product groups and track progression within them. The model using only caudate volume best described advanced disease progression in the combined data set. Contrary to expectations, combining clinical markers and volumetric measures did not improve tracking longitudinal progression.

CONCLUSIONS

Monitoring volumetric changes throughout a trial (alongside primary and secondary clinical end points) may provide a more comprehensive understanding of improvements in functional outcomes and help to improve the design of clinical trials. Alternatively, our results suggest that imaging deserves consideration as an end point in clinical trials because of the prospect of greater sensitivity. © 2021 International Parkinson and Movement Disorder Society.

MRI subcortical segmentation in neurodegeneration with cascaded 3D CNNs

The subcortical structures of the brain are relevant for many neurodegenerative diseases like Huntington's disease (HD). Quantitative segmentation of these structures from magnetic resonance images (MRIs) has been studied in clinical and neuroimaging research. Recently, convolutional neural networks (CNNs) have been successfully used for many medical image analysis tasks, including subcortical segmentation. In this work, we propose a 2-stage cascaded 3D subcortical segmentation framework, with the same 3D CNN architecture for both stages. Attention gates, residual blocks and output adding are used in our proposed 3D CNN. In the first stage, we apply our model to downsampled images to output a coarse segmentation. Next, we crop the extended subcortical region from the original image based on this coarse segmentation, and we input the cropped region to the second CNN to obtain the final segmentation. Left and right pairs of thalamus, caudate, pallidum and putamen are considered in our segmentation. We use the Dice coefficient as our metric and evaluate our method on two datasets: the publicly available IBSR dataset and a subset of the PREDICT-HD database, which includes healthy controls and HD subjects. We train our models on only healthy control subjects and test on both healthy controls and HD subjects to examine model generalizability. Compared with the state-of-the-art methods, our method has the highest mean Dice score on all considered subcortical structures (except the thalamus on IBSR), with more pronounced improvement for HD subjects. This suggests that our method may have better ability to segment MRIs of subjects with neurodegenerative disease.

Longitudinal subcortical segmentation with deep learning

Longitudinal information is important for monitoring the progression of neurodegenerative diseases, such as Huntington's disease (HD). Specifically, longitudinal magnetic resonance imaging (MRI) studies may allow the discovery of subtle intra-subject changes over time that may otherwise go undetected because of inter-subject variability. For HD patients, the primary imaging-based marker of disease progression is the atrophy of subcortical structures, mainly the caudate and putamen. To better understand the course of subcortical atrophy in HD and its correlation with clinical outcome measures, highly accurate segmentation is important. In recent years, subcortical segmentation methods have moved towards deep learning, given the state-of-the-art accuracy and computational efficiency provided by these models. However, these methods are not designed for longitudinal analysis, but rather treat each time point as an independent sample, discarding the longitudinal structure of the data. In this paper, we propose a deep learning based subcortical segmentation method that takes into account this longitudinal information. Our method takes a longitudinal pair of 3D MRIs as input, and jointly computes the corresponding segmentations. We use bi-directional convolutional long short-term memory (C-LSTM) blocks in our model to leverage the longitudinal information between scans. We test our method on the PREDICT-HD dataset and use the Dice coefficient, average surface distance and 95-percent Hausdorff distance as our evaluation metrics. Compared to cross-sectional segmentation, we improve the overall accuracy of segmentation, and our method has more consistent performance across time points. Furthermore, our method identifies a stronger correlation between subcortical volume loss and decline in the total motor score, an important clinical outcome measure for HD.

Moderate Intensity Exercise in Pre-manifest Huntington's Disease: Results of a 6 months Trial

BACKGROUND

While it has been shown that aerobic exercise interventions are well tolerated in participants with the Huntington disease (HD) gene mutation, no study to date has tested whether an aerobic exercise intervention benefits brain structure and function in pre-manifest HD.

OBJECTIVE

In this study we utilized magnetic resonance (MR) imaging techniques to assess the efficacy of moderate-to-vigorous exercise treatment relative to active stretching and toning control.

METHODS

Forty pre-manifest participants with confirmed HD gene expansion were recruited into a two-arm intervention study that included a moderate-to-vigorous intensity home-based walking exercise intervention (N=34) and an active stretching and toning control intervention (N=6). Participants were assessed at baseline and after 26 weeks in one of the two study arms.

RESULTS

25 of the 34 (74%) participants assigned to the moderate-to-vigorous intensity group completed the intervention while 4 of the 6 (67%) participants in the stretching and toning intervention completed the study. The primary analyses compared the two arms of the study and found no statistical differences between the groups. Both groups were found to have improved their cardiorespiratory fitness as assessed by maximal oxygen uptake (VO₂max). A secondary analysis combined the two arms of the study and there was a significant relationship (p<0.05) between change in VO₂max and change in brain structure.

CONCLUSIONS

Though this study did not show efficacy for the exercise intervention, secondary results suggest that aerobic exercise interventions increasing cardiorespiratory fitness may be a potential way to slow progression in pre-manifest HD.

Responsiveness to change over time and test-retest reliability of the PROMIS and Neuro-QoL mental health measures in persons with Huntington disease (HD)

BACKGROUND

The majority of persons with Huntington disease (HD) experience mental health symptoms. Patient-reported outcome (PRO) measures are capable of capturing unobservable behaviors and feelings relating to mental health. The current study aimed to test the reliability and responsiveness to self-reported and clinician-rated change over time of Neuro-QoL and PROMIS mental health PROs over the course of a 24-month period.

METHODS

At baseline, 12-months, and 24-months, 362 participants with premanifest or manifest HD completed the Neuro-QoL Depression computer adaptive test (CAT), PROMIS Depression short form (SF), Neuro-QoL Anxiety CAT, PROMIS Anxiety SF, PROMIS Anger CAT and SF, Neuro-QoL Emotional/Behavioral Dyscontrol CAT and SF, Neuro-QoL Positive Affect and Well-Being CAT and SF, and Neuro-QoL Stigma CAT and SF. Participants completed several clinician-administered measures at each time point, as well as several global ratings of change at 12- and 24-months. Reliability (test-retest reliability and measurement error) and responsiveness (using standardized response means and general linear models) were assessed.

RESULTS

Test-retest reliability and measurement error were excellent for all PROs (all ICC ≥ .90 for test-retest reliability and all SEM percentages ≤ 6.82%). In addition, 12- and 24-month responsiveness were generally supported for the Neuro-QoL and PROMIS mental health PROs; findings relative to clinician-rated anchors of change (e.g., SRMs for the group with declines ranged from .38 to .91 for 24-month change and .09 to .45, with the majority above .25 for 12-month change) were generally more robust than those relative to self-reported anchors of change (e.g., SRMs for the group with declines ranged from .02 to .75, with the majority above .39 for 24-month change and .09 to .45, with the majority above .16 for 12-month change).

CONCLUSIONS

The Neuro-QoL and PROMIS mental health PROs demonstrated strong psychometric reliability, as well as responsiveness to self-reported and clinician-rated change over time in people with HD.

Generalizing MRI Subcortical Segmentation to Neurodegeneration

Many neurodegenerative diseases like Huntington's disease (HD) affect the subcortical structures of the brain, especially the caudate and the putamen. Automated segmentation of subcortical structures from MRI scans is thus important in HD studies. LiviaNET [2] is the state-of-the-art deep learning approach for subcortical segmentation. As all learning-based models, this approach requires appropriate training data. While annotated healthy control images are relatively easy to obtain, generating such annotations for each new disease population can be prohibitively expensive. In this work, we explore LiviaNET variants using well-known strategies for improving performance, to make it more generalizable to patients with substantial neurodegeneration. Specifically, we explored Res-blocks in our convolutional neural network, and we also explored manipulating the input to the network as well as random elastic deformations for data augmentation. We tested our method on images from the PREDICT-HD dataset, which includes control and HD subjects. We trained on control subjects and tested on both controls and HD patients. Compared to the original LiviaNET, we improved the accuracy of most structures, both for controls and for HD patients. The caudate has the most pronounced improvement in HD subjects with the proposed modifications to LiviaNET, which is noteworthy since caudate is known to be severely atrophied in HD. This suggests our extensions may improve the generalization ability of LiviaNET to cohorts where significant neurodegeneration is present, without needing to be retrained.

Patch-Based Abnormality Maps for Improved Deep Learning-Based Classification of Huntington's Disease

Deep learning techniques have demonstrated state-of-the-art performances in many medical imaging applications. These methods can efficiently learn specific patterns. An alternative approach to deep learning is patch-based grading methods, which aim to detect local similarities and differences between groups of subjects. This latter approach usually requires less training data compared to deep learning techniques. In this work, we propose two major contributions: first, we combine patch-based and deep learning methods. Second, we propose to extend the patch-based grading method to a new patch-based abnormality metric. Our method enables us to detect localized structural abnormalities in a test image by comparison to a template library consisting of images from a variety of healthy controls. We evaluate our method by comparing classification performance using different sets of features and models. Our experiments show that our novel patch-based abnormality metric increases deep learning performance from 91.3% to 95.8% of accuracy compared to standard deep learning approaches based on the MRI intensity.

Validation of Neuro-QoL and PROMIS Mental Health Patient Reported Outcome Measures in Persons with Huntington Disease

BACKGROUND

Patient-reported outcomes (PROs) for mental health are important for persons with Huntington disease (HD) who commonly experience symptoms of depression, anxiety, irritability, anger, aggression, and apathy. Given this, there is a need for reliable and valid patient-reported outcomes measures of mental health for use as patient-centered outcomes in clinical trials.

OBJECTIVE

Thus, the purpose of this study was to establish the psychometric properties (i.e., reliability and validity) of six Neuro-QoL and PROMIS mental health measures to support their clinical utility in persons with HD.

METHODS

294 individuals with premanifest (n = 102) or manifest HD (n = 131 early HD; n = 61 late HD) completed Neuro-QoL/PROMIS measures of Emotional and Behavioral Dyscontrol, Positive Affect and Well-Being, Stigma, Anger, Anxiety, and Depression, legacy measures of self-reported mental health, and clinician-rated assessments of functioning.

RESULTS

Convergent validity and discriminant validity for the Neuro-QoL and PROMIS measures of Emotional and Behavioral Dyscontrol, Positive Affect and Well-Being, Stigma, Anger, Anxiety, and Depression, were supported in persons with HD. Neuro-QoL measures of Anxiety and Depression also demonstrated moderate sensitivity and specificity (i.e., they were able to distinguish between individuals with and without clinically significant anxiety and depression).

CONCLUSIONS

Findings provide psychometric support for the clinical utility of the Neuro-QoL/PROMIS measures of mental health measures in persons with HD. As such, these measures should be considered for the standardized assessment of health-related quality of life in persons with HD.

Genetic Risk Underlying Psychiatric and Cognitive Symptoms in Huntington's Disease

BACKGROUND

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the HTT gene. It is diagnosed following a standardized examination of motor control and often presents with cognitive decline and psychiatric symptoms. Recent studies have detected genetic loci modifying the age at onset of motor symptoms in HD, but genetic factors influencing cognitive and psychiatric presentations are unknown.

METHODS

We tested the hypothesis that psychiatric and cognitive symptoms in HD are influenced by the same common genetic variation as in the general population by 1) constructing polygenic risk scores from large genome-wide association studies of psychiatric and neurodegenerative disorders and of intelligence and 2) testing for correlation with the presence of psychiatric and cognitive symptoms in a large sample (n = 5160) of patients with HD.

RESULTS

Polygenic risk score for major depression was associated specifically with increased risk of depression in HD, as was schizophrenia risk score with psychosis and irritability. Cognitive impairment and apathy were associated with reduced polygenic risk score for intelligence.

CONCLUSIONS

Polygenic risk scores for psychiatric disorders, particularly depression and schizophrenia, are associated with increased risk of the corresponding psychiatric symptoms in HD, suggesting a common genetic liability. However, the genetic liability to cognitive impairment and apathy appears to be distinct from other psychiatric symptoms in HD. No associations were observed between HD symptoms and risk scores for other neurodegenerative disorders. These data provide a rationale for treatments effective in depression and schizophrenia to be used to treat depression and psychotic symptoms in HD.

Understanding domains that influence perceived stigma in individuals with Huntington disease

PURPOSE/OBJECTIVE

Persons with Huntington's disease experience stigma because of their gene status. Whereas perceived stigma has been found to impact quality of life, it is unknown how different health domains (i.e., physical, emotional, cognitive, and social) are associated with feelings of stigma. In addition, stigma research has been limited by the use of cross-sectional analyses. The current study seeks to explore which domains are associated with stigma in a longitudinal assessment of persons with Huntington's disease. Research Method/Design: The current analysis used data from the HDQLIFE study, which included 479 participants at baseline, 315 participants at 12 months, and 277 participants at 24 months. A multilevel model (time nested within person) was used to examine the effect of physical, emotional, cognitive, and social health on perceived stigma (Neuro-QoL Stigma) while controlling for demographic factors.

RESULTS

Findings indicate that physical, emotional, and cognitive health were associated with perceived stigma, whereas social health and demographic factors were not. Within-subject, time-varying predictors accounted for 20.2% of the variance in stigma.

CONCLUSIONS/IMPLICATIONS

Our findings suggest that perceived stigma is influenced by physical, emotional, and cognitive health, which may be treated with physical therapy, emotional counseling, and cognitive rehabilitation. Application of these therapies may relieve the burden of perceived stigma; however, more research is needed in this area. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Predicting an optimal composite outcome variable for Huntington's disease clinical trials

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.

Positive Affect and Well-Being in Huntington's Disease Moderates the Association Between Functional Impairment and HRQOL Outcomes

BACKGROUND

Positive affect is associated with resiliency and beneficial health outcomes, but little is known about associations between positive affect and health-related quality of life (HRQOL) in Huntington's disease (HD).

OBJECTIVE

This longitudinal study determined the association between positive affect and several HRQOL outcomes in persons with HD. Functional status was examined as a moderator of the association between positive affect and HRQOL.

METHODS

Participants, with premanifest (i.e., genetically at risk but no clinical diagnosis, n = 50) and manifest HD (early-stage n = 171; late-stage n = 101), completed a measure of positive affect and well-being and several HRQOL measures at baseline, 12-, and 24-month follow-ups. UHDRS Functional Assessment scale indicated functional status.

RESULTS

Positive affect was associated with better HRQOL for persons with premanifest and manifest HD over the 24-month time frame. These associations were moderated by functional status. For persons with higher functional status, positive affect was associated with better HRQOL, including less depression, lower anxiety, less anger, better social role satisfaction, better executive functions, greater upper extremity function, less dyscontrol, and less concern with death and dying. For persons with lower functional status, positive affect was not associated with HRQOL.

CONCLUSIONS

Positive affect predicted better self-reported HRQOL over a 24-month period in persons with premanifest and manifest HD, particularly when participnats had better functional status. Interventions to enhance positive affect in HD may have beneficial effects on HRQOL.

TENSOR-BASED GRADING: A NOVEL PATCH-BASED GRADING APPROACH FOR THE ANALYSIS OF DEFORMATION FIELDS IN HUNTINGTON'S DISEASE

The improvements in magnetic resonance imaging have led to the development of numerous techniques to better detect structural alterations caused by neurodegenerative diseases. Among these, the patch-based grading framework has been proposed to model local patterns of anatomical changes. This approach is attractive because of its low computational cost and its competitive performance. Other studies have proposed to analyze the deformations of brain structures using tensor-based morphometry, which is a highly interpretable approach. In this work, we propose to combine the advantages of these two approaches by extending the patch-based grading framework with a new tensor-based grading method that enables us to model patterns of local deformation using a log-Euclidean metric. We evaluate our new method in a study of the putamen for the classification of patients with pre-manifest Huntington's disease and healthy controls. Our experiments show a substantial increase in classification accuracy (87.5 ± 0.5 vs. 81.3 ± 0.6) compared to the existing patch-based grading methods, and a good complement to putamen volume, which is a primary imaging-based marker for the study of Huntington's disease.

Robust Markers and Sample Sizes for Multicenter Trials of Huntington Disease

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

Disease Progression in Huntington Disease: An Analysis of Multiple Longitudinal Outcomes

BACKGROUND

Critical to discovering targeted therapies for Huntington disease (HD) are validated methods that more precisely predict when clinical outcomes occur for different patient profiles.

OBJECTIVE

To more precisely predict the probability of when motor diagnosis (diagnostic confidence level 4) on the Unified Huntington's Disease Rating Scale (UHDRS), cognitive impairment (two or more neuropsychological scores on the UHDRS were 1.5 standard deviations below normative means) and Stage II Total Functional Capacity (TFC) first occur by accounting for dependencies between these outcomes.

METHODS

Adult premanifest participants with ≥36 CAG repeats were selected from multi-center, longitudinal, observational studies: Prospective Huntington At Risk Observational Study (PHAROS, n = 346), Neurobiological Predictors of Huntington Disease (PREDICT, n = 909); and Cooperative Huntington Observational Research Trial (COHORT, n = 430). Probabilities were estimated for each study, and pooled using the Joint Progression of Risk Assessment Tool (JPRAT) which accounts for dependencies between outcomes.

RESULTS

All studies had similar probabilities of when motor diagnosis, cognitive impairment, and Stage II TFC first occurred. Probability estimates from JPRAT were 43% less variable than from models that ignored dependencies between outcomes. The probability of experiencing motor-diagnosis, cognitive impairment, and Stage II TFC within 5 years was 10%, 18%, and 7%, respectively for 45-year-olds with 42 CAG repeats, and was 4%, 10% and 5%, respectively, for 40 year olds with 42 CAG repeats.

CONCLUSIONS

Improved predictions from JPRAT may benefit treatment studies of rare diseases and is an alternative to composite outcomes when the objective is interpreting individual outcomes within the same model.

How different aspects of motor dysfunction influence day-to-day function in huntington's disease

PURPOSE

This study examined the relationships between different aspects of motor dysfunction (chorea, dystonia, rigidity, incoordination, oculomotor dysfunction, dysarthria, and gait difficulties) and functional status in persons with Huntington's disease.

METHODS

A total of 527 persons with Huntington's disease completed the Unified Huntington's Disease Rating Scale motor, total functional capacity, and functional assessments.

RESULTS

Confirmatory factor analysis indicated that a 4-factor model provided a better model fit than the existing 5-factor model. Exploratory factor analysis identified the following 4 factors from the motor scale: dystonia, chorea, rigidity, and a general motor factor. Regression indicated that dystonia (β = -0.47 and -0.79) and rigidity (β = -0.28 and -0.59) had strong associations with function, whereas chorea had modest correlations (β = -0.16 and -0.15).

CONCLUSIONS

Dystonia and rigidity have stronger relationships with functional status than chorea in persons with Huntington's disease. The findings underscore the need for further research regarding the effects of dystonia and rigidity on functioning. © 2019 International Parkinson and Movement Disorder Society.

Suicidal Ideation Assessment in Individuals with Premanifest and Manifest Huntington Disease

BACKGROUND

Huntington disease (HD) is associated with increased risk of suicide.

OBJECTIVE

This study compares suicide ideation in HD to the general population, assesses factors associated with increased prevalence of suicidal thoughts, and compares clinician-rated to self-reported assessments of suicidal ideation.

METHODS

We examined 496 participants with premanifest or manifest HD. Clinician-rated suicidal ideation was measured using the Problem Behaviors Assessment - short form. Self-reported ideation was measured using two items from the HDQLIFE Concern with Death and Dying item bank. Independent sample t-tests were conducted to compare the prevalence of suicidal thoughts between our HD sample and the U.S.

POPULATION

Logistic regression analyses were used to determine characteristics associated with higher odds of clinically significant suicidal ideation. Kappa agreement coefficients were calculated to evaluate concurrence between clinician-rated and self-reported assessments.

RESULTS

Our sample had a significantly higher occurrence of suicidal ideation (19.76%) and suicidal plans (2.1%) than the general population (p < 0.0001). Odds of clinically significant suicidal ideation were 6.8 times higher in females (p = 0.04) on the clinician measure, and Hispanic/Latinos had 10.9 times higher odds than non-Hispanics (p = 0.025) on the self-report measure. Clinician-rated assessment had fair agreement (k = 0.2-0.4) with self-reported assessments, except in early stage HD where there was no overlap in the identification of participants with clinically significant suicidal ideation.

DISCUSSION

Assessment for suicidal ideation and clinically significant suicidal thoughts in HD with a multimodal approach that includes clinician-rated and self-report measures is critical at all stages of the disease.

CAG Repeat Not Polyglutamine Length Determines Timing of Huntington's Disease Onset

Variable, glutamine-encoding, CAA interruptions indicate that a property of the uninterrupted HTT CAG repeat sequence, distinct from the length of huntingtin's polyglutamine segment, dictates the rate at which Huntington's disease (HD) develops. The timing of onset shows no significant association with HTT cis-eQTLs but is influenced, sometimes in a sex-specific manner, by polymorphic variation at multiple DNA maintenance genes, suggesting that the special onset-determining property of the uninterrupted CAG repeat is a propensity for length instability that leads to its somatic expansion. Additional naturally occurring genetic modifier loci, defined by GWAS, may influence HD pathogenesis through other mechanisms. These findings have profound implications for the pathogenesis of HD and other repeat diseases and question the fundamental premise that polyglutamine length determines the rate of pathogenesis in the "polyglutamine disorders."

End-of-life measures in Huntington disease: HDQLIFE Meaning and Purpose, Concern with Death and Dying, and End of Life Planning

BACKGROUND AND PURPOSE

Huntington disease (HD) is a progressive neurodegenerative disorder. There are no HD-specific measures to assess for end-of-life (EOL) preferences that have been validated for clinical use. The purpose of this study is to demonstrate reliability and validity of three HD-specific EOL measures for use in and clinical research settings.

METHODS

We examined internal reliability, test-retest reliability, floor and ceiling effects, convergent and discriminant validity, known groups' validity, measurement error, and change over time to systematically examine reliability and validity of the HDQLIFE EOL measures.

RESULTS

Internal consistency and test-retest reliability were > 0.70. The measures were generally free of floor and ceiling effects and measurement error was minimal. Convergent and discriminant validity were consistent with well-known constructs in the field. Hypotheses for known groups validity were partially supported (there were generally group differences for the EOL planning measures, but not for meaning and purpose or concern with death and dying). Measurement error was acceptable and there were minimal changes over time across the EOL measures.

CONCLUSIONS

Results support the clinical utility of the HDQLIFE EOL measures in persons with HD.

Sample enrichment for clinical trials to show delay of onset in huntington disease

BACKGROUND

Disease-modifying clinical trials in persons without symptoms are often limited in methods to assess the impact associated with experimental therapeutics. This study suggests sample enrichment approaches to facilitate preventive trials to delay disease onset in individuals with the dominant gene for Huntington disease.

METHODS

Using published onset prediction indexes, we conducted the receiver operating curve analysis for diagnosis within a 3-year clinical trial time frame. We determined optimal cut points on the indexes for participant recruitment and then conducted sample size and power calculations to detect varying effect sizes for treatment efficacy in reducing 3-year rates of disease onset (or diagnosis).

RESULTS

Area under the curve for 3 onset prediction indexes all demonstrated excellent value in sample enrichment methodology, with the best-performing index being the multivariate risk score (MRS).

CONCLUSIONS

This study showed that conducting an intervention trial in premanifest and prodromal individuals with the gene expansion for Huntington disease is highly feasible using sample enrichment recruitment methods. Ongoing natural history studies are highly likely to indicate additional markers of disease prior to diagnosis. Statistical modeling of identified markers can facilitate participant enrichment to increase the likelihood of detecting a difference between treatment arms in a cost-effective and efficient manner. Such variations may expedite translation of emerging therapies to persons in an earlier phase of the disease.

TRIAL REGISTRATION

PREDICT-HD is registered with www.clinicaltrials.gov, number NCT00051324. © 2019 International Parkinson and Movement Disorder Society.

Dynamic functional network connectivity in Huntington's disease and its associations with motor and cognitive measures

Dynamic functional network connectivity (dFNC) is an expansion of traditional, static FNC that measures connectivity variation among brain networks throughout scan duration. We used a large resting-state fMRI (rs-fMRI) sample from the PREDICT-HD study (N = 183 Huntington disease gene mutation carriers [HDgmc] and N = 78 healthy control [HC] participants) to examine whole-brain dFNC and its associations with CAG repeat length as well as the product of scaled CAG length and age, a variable representing disease burden. We also tested for relationships between functional connectivity and motor and cognitive measurements. Group independent component analysis was applied to rs-fMRI data to obtain whole-brain resting state networks. FNC was defined as the correlation between RSN time-courses. Dynamic FNC behavior was captured using a sliding time window approach, and FNC results from each window were assigned to four clusters representing FNC states, using a k-means clustering algorithm. HDgmc individuals spent significantly more time in State-1 (the state with the weakest FNC pattern) compared to HC. However, overall HC individuals showed more FNC dynamism than HDgmc. Significant associations between FNC states and genetic and clinical variables were also identified. In FNC State-4 (the one that most resembled static FNC), HDgmc exhibited significantly decreased connectivity between the putamen and medial prefrontal cortex compared to HC, and this was significantly associated with cognitive performance. In FNC State-1, disease burden in HDgmc participants was significantly associated with connectivity between the postcentral gyrus and posterior cingulate cortex, as well as between the inferior occipital gyrus and posterior parietal cortex.

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.

Regional subcortical shape analysis in premanifest Huntington's disease

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.

Understanding patient-reported outcome measures in Huntington disease: at what point is cognitive impairment related to poor measurement reliability?

PURPOSE

Symptom progression in Huntington disease (HD) is associated with cognitive decline which may interfere with the self-report of symptoms. Unfortunately, data to support or refute the psychometric reliability of patient-reported outcomes (PROs) as HD progresses are limited. This is problematic given that PROs are increasingly recognized as important measures of efficacy for new treatments.

METHODS

We examined PRO data from the HDQLIFE Measurement System (Speech Difficulties; Swallowing Difficulties; Chorea) in 509 individuals with premanifest, early-stage, or late-stage HD. Clinician-administered assessments of motor functioning (items from the UHDRS) and standardized objective assessments of cognition (Stroop, Symbol Digit Modalities) were also collected. We examined item bias using differential item functioning (DIF) across HD stage (premanifest, early-, late-) and relative to cognitive performance. We also examined the correlations between self-report and clinician ratings. Regression models that considered total cognitive ability were utilized to determine psychometric reliability of the PROs.

RESULTS

Most PRO items were free from DIF for both staging and cognition. There were modest correlations between PROs and clinician report (ranged from - 0.40 to - 0.60). Modeling analyses indicated that psychometric reliability breaks down with poorer cognition and more progressed disease stage; split-half reliability was compromised (i.e., split-half reliability < 0.80) when scores were < 136 for Chorea, < 109 for Speech Difficulties, and < 179 for Swallowing Difficulties.

CONCLUSIONS

Results indicate that the psychometric reliability of PROs can be compromised as HD symptoms progress and cognition declines. Clinicians should consider PROs in conjunction with other types of assessments when total cognition scores exceed critical thresholds.

Genetic Modification of Huntington Disease Acts Early in the Prediagnosis Phase

Age at onset of Huntington disease, an inherited neurodegenerative disorder, is influenced by the size of the disease-causing CAG trinucleotide repeat expansion in HTT and by genetic modifier loci on chromosomes 8 and 15. Stratifying by modifier genotype, we have examined putamen volume, total motor score (TMS), and symbol digit modalities test (SDMT) scores, both at study entry and longitudinally, in normal controls and CAG-expansion carriers who were enrolled prior to the emergence of manifest HD in the PREDICT-HD study. The modifiers, which included onset-hastening and onset-delaying alleles on chromosome 15 and an onset-hastening allele on chromosome 8, revealed no major effect in controls but distinct patterns of modification in prediagnosis HD subjects. Putamen volume at study entry showed evidence of reciprocal modification by the chromosome 15 alleles, but the rate of loss of putamen volume was modified only by the deleterious chromosome 15 allele. By contrast, both alleles modified the rate of change of the SDMT score, but neither had an effect on the TMS. The influence of the chromosome 8 modifier was evident only in the rate of TMS increase. The data indicate that (1) modification of pathogenesis can occur early in the prediagnosis phase, (2) the modifier loci act in genetic interaction with the HD mutation rather than through independent additive effects, and (3) HD subclinical phenotypes are differentially influenced by each modifier, implying distinct effects in different cells or tissues. Together, these findings indicate the potential benefit of using genetic modifier strategies for dissecting the prediagnosis pathogenic process in HD.

High and Low Levels of an NTRK2-Driven Genetic Profile Affect Motor- and Cognition-Associated Frontal Gray Matter in Prodromal Huntington's Disease

This study assessed how BDNF (brain-derived neurotrophic factor) and other genes involved in its signaling influence brain structure and clinical functioning in pre-diagnosis Huntington's disease (HD). Parallel independent component analysis (pICA), a multivariate method for identifying correlated patterns in multimodal datasets, was applied to gray matter concentration (GMC) and genomic data from a sizeable PREDICT-HD prodromal cohort (N = 715). pICA identified a genetic component highlighting NTRK2, which encodes BDNF's TrkB receptor, that correlated with a GMC component including supplementary motor, precentral/premotor cortex, and other frontal areas (p < 0.001); this association appeared to be driven by participants with high or low levels of the genetic profile. The frontal GMC profile correlated with cognitive and motor variables (Trail Making Test A (p = 0.03); Stroop Color (p = 0.017); Stroop Interference (p = 0.04); Symbol Digit Modalities Test (p = 0.031); Total Motor Score (p = 0.01)). A top-weighted NTRK2 variant (rs2277193) was protectively associated with Trail Making Test B (p = 0.007); greater minor allele numbers were linked to a better performance. These results support the idea of a protective role of NTRK2 in prodromal HD, particularly in individuals with certain genotypes, and suggest that this gene may influence the preservation of frontal gray matter that is important for clinical functioning.

A Fully-Automated Subcortical and Ventricular Shape Generation Pipeline Preserving Smoothness and Anatomical Topology

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.

Genetics Modulate Gray Matter Variation Beyond Disease Burden in Prodromal Huntington's Disease

Huntington’s disease (HD) is a neurodegenerative disorder caused by an expansion mutation of the cytosine–adenine–guanine (CAG) trinucleotide in the HTT gene. Decline in cognitive and motor functioning during the prodromal phase has been reported, and understanding genetic influences on prodromal disease progression beyond CAG will benefit intervention therapies. From a prodromal HD cohort (N = 715), we extracted gray matter (GM) components through independent component analysis and tested them for associations with cognitive and motor functioning that cannot be accounted for by CAG-induced disease burden (cumulative effects of CAG expansion and age). Furthermore, we examined genetic associations (at the genomic, HD pathway, and candidate region levels) with the GM components that were related to functional decline. After accounting for disease burden, GM in a component containing cuneus, lingual, and middle occipital regions was positively associated with attention and working memory performance, and the effect size was about a tenth of that of disease burden. Prodromal participants with at least one dystonia sign also had significantly lower GM volume in a bilateral inferior parietal component than participants without dystonia, after controlling for the disease burden. Two single-nucleotide polymorphisms (SNPs: rs71358386 in NCOR1 and rs71358386 in ADORA2B) in the HD pathway were significantly associated with GM volume in the cuneus component, with minor alleles being linked to reduced GM volume. Additionally, homozygous minor allele carriers of SNPs in a candidate region of ch15q13.3 had significantly higher GM volume in the inferior parietal component, and one minor allele copy was associated with a total motor score decrease of 0.14 U. Our findings depict an early genetical GM reduction in prodromal HD that occurs irrespective of disease burden and affects regions important for cognitive and motor functioning.

Whole-Brain Connectivity in a Large Study of Huntington's Disease Gene Mutation Carriers and Healthy Controls

Huntington's disease (HD) is an inherited brain disorder characterized by progressive motor, cognitive, and behavioral dysfunctions. It is caused by abnormally large trinucleotide cytosine-adenine-guanine (CAG) repeat expansions on exon 1 of the Huntingtin gene. CAG repeat length (CAG-RL) inversely correlates with an earlier age of onset. Region-based studies have shown that HD gene mutation carrier (HDgmc) individuals (CAG-RL ≥36) present functional connectivity alterations in subcortical (SC) and default mode networks. In this analysis, we expand on previous HD studies by investigating associations between CAG-RL and connectivity in the whole brain, as well as between CAG-dependent connectivity and motor and cognitive performances. We used group-independent component analysis on resting-state functional magnetic resonance imaging scans of 261 individuals (183 HDgmc and 78 healthy controls) from the PREDICT-HD study, to obtain whole-brain resting state networks (RSNs). Regression analysis was applied within and between RSNs connectivity (functional network connectivity [FNC]) to identify CAG-RL associations. Connectivity within the putamen RSN is negatively correlated with CAG-RL. The FNC between putamen and insula decreases with increasing CAG-RL, and also shows significant associations with motor and cognitive measures. The FNC between calcarine and middle frontal gyri increased with CAG-RL. In contrast, FNC in other visual (VIS) networks declined with increasing CAG-RL. In addition to observed effects in SC areas known to be related to HD, our study identifies a strong presence of alterations in VIS regions less commonly observed in previous reports and provides a step forward in understanding FNC dysfunction in HDgmc.

Understanding the need for assistance with survey completion in people with Huntington disease

PURPOSE

In Huntington disease (HD), motor, cognitive, and psychiatric changes can have a detrimental impact on health-related quality of life (HRQOL). The purpose of this paper is to describe the extent and type of assistance needed to complete online HRQOL surveys, and the impact of assistance on HRQOL scores.

METHODS

A patient-reported outcome measurement system was developed for HD-specific HRQOL. Individuals across the prodromal and diagnosed disease severity spectrum (n = 532) completed surveys by computer, and reported the amount and type of assistance they received.

RESULTS

Some participants (n = 56; 10.5%) did not complete all surveys; this group had larger proportions with late stage disease, racial/ethnic minority status, low education and single marital status, and poorer motor, independence and cognitive function compared to those who completed all surveys (n = 476). Overall, 72% of individuals did not receive assistance, 11% received computer assistance only, and 17% received assistance answering the survey questions. The majority of late stage individuals (78%) received some assistance compared to early stage (29%) and prodromal individuals (< 1%). Those who received assistance had higher proportions with late stage disease, were older, had less education, and had poorer functional and cognitive skills. Before and after adjustment for sociodemographic and clinical characteristics, those who received assistance had poorer scores on some HRQOL outcomes than those who did not receive assistance.

CONCLUSIONS

Computer-based assessments are feasible for many persons with HD, although other methods may also be needed. Clinicians and researchers should develop strategies to assist people with HD to complete HRQOL surveys.

Evaluating cognition in individuals with Huntington disease: Neuro-QoL cognitive functioning measures

PURPOSE

Cognitive functioning impacts health-related quality of life (HRQOL) for individuals with Huntington disease (HD). The Neuro-QoL includes two patient-reported outcome (PRO) measures of cognition-Executive Function (EF) and General Concerns (GC). These measures have not previously been validated for use in HD. The purpose of this analysis is to evaluate the reliability and validity of the Neuro-QoL Cognitive Function measures for use in HD.

METHODS

Five hundred ten individuals with prodromal or manifest HD completed the Neuro-QoL Cognition measures, two other PRO measures of HRQOL (WHODAS 2.0 and EQ5D), and a depression measure (PROMIS Depression). Measures of functioning The Total Functional Capacity and behavior (Problem Behaviors Assessment) were completed by clinician interview. Objective measures of cognition were obtained using clinician-administered Symbol Digit Modalities Test and the Stroop Test (Word, Color, and Interference). Self-rated, clinician-rated, and objective composite scores were developed. We examined the Neuro-QoL measures for reliability, convergent validity, discriminant validity, and known-groups validity.

RESULTS

Excellent reliabilities (Cronbach's alphas ≥ 0.94) were found. Convergent validity was supported, with strong relationships between self-reported measures of cognition. Discriminant validity was supported by less robust correlations between self-reported cognition and other constructs. Prodromal participants reported fewer cognitive problems than manifest groups, and early-stage HD participants reported fewer problems than late-stage HD participants.

CONCLUSIONS

The Neuro-QoL Cognition measures provide reliable and valid assessments of self-reported cognitive functioning for individuals with HD. Findings support the utility of these measures for assessing self-reported cognition.

MicroRNAs in CSF as prodromal biomarkers for Huntington disease in the PREDICT-HD study

OBJECTIVE

To investigate the feasibility of microRNA (miRNA) levels in CSF as biomarkers for prodromal Huntington disease (HD).

METHODS

miRNA levels were measured in CSF from 60 PREDICT-HD study participants using the HTG protocol. Using a CAG-Age Product score, 30 prodromal HD participants were selected based on estimated probability of imminent clinical diagnosis of HD (i.e., low, medium, high; n = 10/group). For comparison, participants already diagnosed (n = 15) and healthy controls (n = 15) were also selected.

RESULTS

A total of 2,081 miRNAs were detected and 6 were significantly increased in the prodromal HD gene expansion carriers vs controls at false discovery rate q < 0.05 (miR-520f-3p, miR-135b-3p, miR-4317, miR-3928-5p, miR-8082, miR-140-5p). Evaluating the miRNA levels in each of the HD risk categories, all 6 revealed a pattern of increasing abundance from control to low risk, and from low risk to medium risk, which then leveled off from the medium to high risk and HD diagnosed groups.

CONCLUSIONS

This study reports miRNAs as CSF biomarkers of prodromal and diagnosed HD. Importantly, miRNAs were detected in the prodromal HD groups furthest from diagnosis where treatments are likely to be most consequential and meaningful. The identification of potential biomarkers in the disease prodrome may prove useful in evaluating treatments that may postpone disease onset.

CLINICALTRIALSGOV IDENTIFIER

NCT00051324.

Relationships Among Apathy, Health-Related Quality of Life, and Function in Huntington's Disease

Up to 90% of individuals with Huntington's disease (HD)-a progressive, inherited neurodegenerative disorder-experience apathy. Apathy is particularly debilitating because it is marked by a reduction in goal-directed behaviors, including self-care, social interactions, and mobility. The objective of this study was to examine relationships between variables of apathy, functional status, physical function, cognitive function, behavioral status/emotional function, and health-related quality of life. Clinician-rated measures of physical, cognitive, and behavioral function, including one clinician-rated item on apathy, and self-reported measures of physical function, health-related quality of life, and emotional, cognitive, and social function were collected in a single session from 487 persons with the HD mutation (prodromal, N=193; early-stage manifest, N=186; late-stage manifest, N=108). Multiple linear regression models were used to examine which outcomes best predicted clinician-rated apathy after controlling for disease stage. Greater apathy related to less independence, increased motor impairment, and more clinician-rated behavioral problems (i.e., anger, irritability, depression). Similarly, poorer self-reported health-related quality of life; greater chorea; greater upper- and lower-extremity dysfunction; greater speech and swallowing dysfunction; worse anxiety, depression, and behavioral dyscontrol; worse cognitive function; and less satisfaction with social roles related to greater apathy. In conclusion, apathy related to physical, cognitive, and behavioral dysfunction across disease stages. Future work should explore whether clinical interventions targeting different functional domains may have the potential to reduce apathy in this patient population.

Rating scales for cognition in Huntington's disease: Critique and recommendations

Cognitive impairment is one of the main features of Huntington's disease and is present across the disease spectrum. As part of the International Parkinson's Disease and Movement Disorder Society-sponsored project to review all clinical rating scales used in Huntington's disease, a systematic review of the literature was performed to identify cognitive scales used in Huntington's disease and make recommendations for their use. A total of 17 cognitive scales were identified and evaluated. None of the scales met criteria for a "recommended" status. For assessing severity of cognitive dysfunction, the Montreal Cognitive Assessment was "recommended with caveats." The UHDRS Cognitive Assessment, the UHDRS-For Advanced Patients cognitive section, the Alzheimer's Disease Assessment Scale-Cognitive Subscale, the Frontal Assessment Battery, the Mattis Dementia Rating Scale, the Mini-Mental State Examination, and the Repeatable Battery for the Assessment of Neuropsychological Status were "suggested" for evaluating severity of cognitive impairment. The MoCA was "suggested" as a screening tool for cognitive impairment. The major challenge in the assessment of cognition in Huntington's disease is the lack of a formal definition of dementia and/or mild cognitive impairment in this disease. The committee concluded that there is a need to further validate currently available cognitive scales in Huntington's disease, but that it is premature to recommend the development of new scales. Recently developed Huntington's disease-specific scales, such as the Huntington's Disease-Cognitive Assessment Battery, hold promise but require the completion of more comprehensive clinimetric development. © 2017 International Parkinson and Movement Disorder Society.