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IntroductionThe inclusion of premanifest Huntington's Disease (Pre-HD) subjects in clinical trials necessitates selecting those who are near transition to manifest Huntington's disease (Man-HD). We previously determined that plasma neurofilament light (NfL) levels are significantly correlated with predicted years to Man-HD onset, using established formulae. Recently, a new normalized prognostic index (PIN) score for predicting Pre-HD disease progression has been validated. Our objective was to determine whether plasma NfL levels are similarly associated with PIN score and PIN score-derived years to Man-HD onset (PIN-YTO).Method112 individuals (46 Pre-HD, 66 Man-HD) underwent blood sample collection and clinical assessment, inclusive of the Symbol Digit Modalities Test and Unified Huntington's Disease Rating Scale Total Motor Score. Plasma NfL levels were measured using a Meso Scale Discovery assay.ResultsPre-HD and Man-HD cohorts differed by age (p 10 predicted years from Man-HD onset, compared to those ≤10 predicted years.ConclusionsWe have extensively shown that plasma NfL levels are associated with predicted years to manifest HD onset in Pre-HD participants, and present a plasma NfL cut-point that may help exclude far-from-onset Pre-HD patients from clinical trials.

ImportanceOne major advantage of developing large, federally funded networks for clinical research in neurology is the ability to have a trial-ready network that can efficiently conduct scientifically rigorous projects to improve the health of people with neurologic disorders.ObservationsNational Institute of Neurological Disorders and Stroke Network for Excellence in Neuroscience Clinical Trials (NeuroNEXT) was established in 2011 and renewed in 2018 with the goal of being an efficient network to test between 5 and 7 promising new agents in phase II clinical trials. A clinical coordinating center, data coordinating center, and 25 sites were competitively chosen. Common infrastructure was developed to accelerate timelines for clinical trials, including central institutional review board (a first for the National Institute of Neurological Disorders and Stroke), master clinical trial agreements, the use of common data elements, and experienced research sites and coordination centers. During the first 7 years, the network exceeded the goal of conducting 5 to 7 studies, with 9 funded. High interest was evident by receipt of 148 initial applications for potential studies in various neurologic disorders. Across the first 8 studies (the ninth study was funded at end of initial funding period), the central institutional review board approved the initial protocol in a mean (SD) of 59 (21) days, and additional sites were added a mean (SD) of 22 (18) days after submission. The median time from central institutional review board approval to first site activation was 47.5 days (mean, 102.1; range, 1-282) and from first site activation to first participant consent was 27 days (mean, 37.5; range, 0-96). The median time for database readiness was 3.5 months (mean, 4.0; range, 0-8) from funding receipt. In the 4 completed studies, enrollment met or exceeded expectations with 96% overall data accuracy across all sites. Nine peer-reviewed manuscripts were published, and 22 oral presentations or posters and 9 invited presentations were given at regional, national, and international meetings.Conclusions and relevanceNeuroNEXT initiated 8 studies, successfully enrolled participants at or ahead of schedule, collected high-quality data, published primary results in high-impact journals, and provided mentorship, expert statistical, and trial management support to several new investigators. Partnerships were successfully created between government, academia, industry, foundations, and patient advocacy groups. Clinical trial consortia can efficiently and successfully address a range of important neurologic research and therapeutic questions.

BackgroundThere are limited treatments for progressive multiple sclerosis. Ibudilast inhibits several cyclic nucleotide phosphodiesterases, macrophage migration inhibitory factor, and toll-like receptor 4 and can cross the blood-brain barrier, with potential salutary effects in progressive multiple sclerosis.MethodsWe enrolled patients with primary or secondary progressive multiple sclerosis in a phase 2 randomized trial of oral ibudilast (≤100 mg daily) or placebo for 96 weeks. The primary efficacy end point was the rate of brain atrophy, as measured by the brain parenchymal fraction (brain size relative to the volume of the outer surface contour of the brain). Major secondary end points included the change in the pyramidal tracts on diffusion tensor imaging, the magnetization transfer ratio in normal-appearing brain tissue, the thickness of the retinal nerve-fiber layer, and cortical atrophy, all measures of tissue damage in multiple sclerosis.ResultsOf 255 patients who underwent randomization, 129 were assigned to ibudilast and 126 to placebo. A total of 53% of the patients in the ibudilast group and 52% of those in the placebo group had primary progressive disease; the others had secondary progressive disease. The rate of change in the brain parenchymal fraction was -0.0010 per year with ibudilast and -0.0019 per year with placebo (difference, 0.0009; 95% confidence interval, 0.00004 to 0.0017; P=0.04), which represents approximately 2.5 ml less brain-tissue loss with ibudilast over a period of 96 weeks. Adverse events with ibudilast included gastrointestinal symptoms, headache, and depression.ConclusionsIn a phase 2 trial involving patients with progressive multiple sclerosis, ibudilast was associated with slower progression of brain atrophy than placebo but was associated with higher rates of gastrointestinal side effects, headache, and depression. (Funded by the National Institute of Neurological Disorders and Stroke and others; NN102/SPRINT-MS ClinicalTrials.gov number, NCT01982942 .).

The relationship of heavy alcohol consumption (HAC) and smoking to mortality in those with CHD, and mechanisms through which these effects are elicited are not clear. In order to improve our understanding, we examined the relationship of Alcohol T-Scores (ATS), an epigenetic biomarker of chronic HAC, and cg05575921 methylation, a biomarker of smoking intensity, with all-cause mortality and degree of coronary artery obstruction in a cohort of 217 subjects admitted for CHD-related acute coronary syndrome (ACS). We found that 65% of the subjects had ATS values indicative of chronic HAC. ATS values, but not cg05575921 values, were significantly associated (p < 0.02) with subsequent proband death (total of 28 deaths) with a Cox Proportional Hazards model showing a slightly larger effect of ATS levels than age on all-cause mortality survival (overall model, p < 0.003). Subjects in the highest decile of ATS scores had a 2.4-fold increase in the risk for mortality as compared to those in the lowest decile. In contrast, cg05575921 methylation (p < 0.003) but not ATS scores, were significantly inversely associated with degree of obstruction. Only 2 of the 217 subjects were referred for treatment for either smoking or drinking. We conclude that HAC is an underappreciated driver of CHD-related mortality, that those with ACS who smoke are much less likely to have significant obstruction upon cardiac imaging and that substance use treatment may be underutilized in those with CHD. [ABSTRACT FROM AUTHOR]

Currently, clinicians use their judgement and indices such as the Prediction of Alcohol Withdrawal Syndrome Scale (PAWSS) to determine whether patients are admitted to hospitals for consideration of withdrawal syndrome (AWS). However, only a fraction of those admitted will experience severe AWS. Previously, we and others have shown that epigenetic indices, such as the Alcohol T-Score (ATS), can quantify recent alcohol consumption. However, whether these or other alcohol biomarkers, such as carbohydrate deficient transferrin (CDT), could identify those at risk for severe AWS is unknown. To determine this, we first conducted genome-wide DNA methylation analyses of subjects entering and exiting alcohol treatment to identify loci whose methylation quickly reverted as a function of abstinence. We then tested whether methylation at a rapidly reverting locus, cg07375256, or other existing metrics including PAWSS scores, CDT levels, or ATS, could predict outcome in 125 subjects admitted for consideration of AWS. We found that PAWSS did not significantly predict severe AWS nor seizures. However, methylation at cg07375256 (ZSCAN25) and CDT strongly predicted severe AWS with ATS (p < 0.007) and cg07375256 (p < 6 × 10–5) methylation also predicting AWS associated seizures. We conclude that epigenetic methods can predict those likely to experience severe AWS and that the use of these or similar Precision Epigenetic approaches could better guide AWS management. [ABSTRACT FROM AUTHOR]

Background: Clinical trial scenarios can be modeled using data from observational studies, providing critical information for design of real‐world trials. The Huntington's Disease Integrated Staging System (HD‐ISS) characterizes disease progression over an individual's lifespan and allows for flexibility in the design of trials with the goal of delaying progression. Enrichment methods can be applied to the HD‐ISS to identify subgroups requiring smaller estimated sample sizes. Objective: Investigate time to the event of functional decline (HD‐ISS Stage 3) as an endpoint for trials in HD and present sample size estimates after enrichment. Methods: We classified individuals from observational studies according to the HD‐ISS. We assessed the ability of the prognostic index normed (PIN) and its components to predict time to HD‐ISS Stage 3. For enrichment, we formed groups from deciles of the baseline PIN distribution for HD‐ISS Stage 2 participants. We selected enrichment subgroups closer to Stage 3 transition and estimated sample sizes, using delay in the transition time as the effect size. Results: In predicting time to HD‐ISS Stage 3, PIN outperforms its components. Survival curves for each PIN decile show that groups with PIN from 1.48 to 2.74 have median time to Stage 3 of approximately 2 years and these are combined to create enrichment subgroups. Sample size estimates are presented by enrichment subgroup. Conclusions: PIN is predictive of functional decline. A delay of 9 months or more in the transition to Stage 3 for an enriched sample yields feasible sample size estimates, demonstrating that this approach can aid in planning future trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

ObjectivesDiffusivity in white-matter tracts is abnormal throughout the brain in cross-sectional studies of prodromal Huntington's disease. To date, longitudinal changes have not been observed. The present study investigated cross-sectional and longitudinal changes in white-matter diffusivity in relationship to the phase of prodromal Huntington's progression, and compared them with changes in brain volumes and clinical variables that track disease progression.MethodsDiffusion MRI profiles were studied for 2 years in 37 gene-negative controls and 64 prodromal Huntington's disease participants in varied phases of disease progression. To estimate the relative importance of diffusivity metrics in the prodromal phase, group effects were rank ordered relative to those obtained from analyses of brain volumes, motor, cognitive, and sensory variables.ResultsFirst, at baseline diffusivity was abnormal throughout all tracts, especially as individuals approached a manifest Huntington's disease diagnosis. Baseline diffusivity metrics in 6 tracts and basal ganglia volumes best distinguished among the groups. Second, group differences in longitudinal change in diffusivity were localized to the superior fronto-occipital fasciculus, most prominently in individuals closer to a diagnosis. Group differences were also observed in longitudinal changes of most brain volumes, but not clinical variables. Last, increases in motor symptoms across time were associated with greater changes in the superior fronto-occipital fasciculus diffusivity and corpus callosum, cerebrospinal fluid, and lateral ventricle volumes.ConclusionsThese novel findings provide new insights into changes within 2 years in different facets of brain structure and their clinical relevance to changes in symptomatology that is decisive for a manifest Huntington's diagnosis. © 2016 International Parkinson and Movement Disorder Society.

ObjectiveTo determine clinical and biological variables that predict time to initiation of symptomatic therapy in de novo Parkinson's disease patients.MethodsParkinson's Progression Markers Initiative is a longitudinal case-control study of de novo, untreated Parkinson's disease participants at enrolment. Participants contribute a wide range of motor and non-motor measures, including biofluids and imaging biomarkers. The machine learning method of random survival forests was used to examine the ability of baseline variables to predict time to initiation of symptomatic therapy since study enrollment (baseline).ResultsThere were 423 PD participants enrolled in PPMI and 33 initial baseline variables. Cross-validation results showed that the three-predictor subset of disease duration (time from diagnosis to enrollment), the modified Schwab and England activities of daily living scale, and the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) total score modestly predicted time to initiation of symptomatic therapy (C = 0.70, pseudo-R (2) = 0.13). Prediction using the three variables was similar to using the entire set of 33. None of the biological variables increased accuracy of the prediction. A prognostic index for time to initiation of symptomatic therapy was created using the linear and nonlinear effects of the three top variables based on a post hoc Cox model.InterpretationOur findings using a novel machine learning method support previously reported clinical variables that predict time to initiation of symptomatic therapy. However, the inclusion of biological variables did not increase prediction accuracy. Our prognostic index constructed, based on the group-level survival curve can provide an indication of the risk of initiation of ST for PD patients based on functions of the three top predictors.

Huntington disease (HD) is a neurodegenerative condition with prominent motor (including oculomotor), cognitive, and psychiatric effects. While neuropsychological deficits are present in HD, motor impairments may impact performance on neuropsychological measures, especially those requiring a speeded response, as has been demonstrated in multiple sclerosis and schizophrenia. The current study is the first to explore associations between oculomotor functions and neuropsychological performance in HD. Participants with impaired oculomotor functioning performed worse than those with normal oculomotor functioning on cognitive tasks requiring oculomotor involvement, particularly on psychomotor speed tasks, controlling for covariates. Consideration of oculomotor dysfunction on neuropsychological performance is critical, particularly for populations with motor deficits.

ObjectiveAlthough Huntington disease (HD) is caused by an autosomal dominant mutation, its phenotypic presentation differs widely. Variability in clinical phenotypes of HD may reflect the existence of disease subtypes. This hypothesis was tested in prodromal participants from the longitudinal Neurobiological Predictors of Huntington Disease (PREDICT-HD) study.MethodWe performed clustering using longitudinal data assessing motor, cognitive, and depression symptoms. Using data from 521 participants with 2,716 data points, we fit growth mixture models (GMM) that identify groups based on multivariate trajectories.ResultsIn various GMM, different phases of disease progression were partitioned by progression trajectories of motor and cognitive signs, and by overall level of depression symptoms. More progressed motor signs were accompanied by more progressed cognitive signs, but not always by higher levels of depressive symptoms. In several models, there were at least 2 groups with similar trajectories for motor and cognitive signs that showed different levels for depression symptoms-one with a very low level of depression and the other with a higher level of depression.ConclusionsFindings indicate that at least intermediate HD progression might be associated with different levels of depression. Depression is one of the few symptoms that is treatable in HD and has implications for clinical care. Identification of potential depression subtypes may also help to select appropriate patients for clinical trials.

BackgroundIt is well known in Huntington's disease that cytosine-adenine-guanine expansion and age at study entry are predictive of the timing of motor diagnosis. The goal of this study was to assess whether additional motor, imaging, cognitive, functional, psychiatric, and demographic variables measured at study entry increased the ability to predict the risk of motor diagnosis over 12 years.MethodsOne thousand seventy-eight Huntington's disease gene-expanded carriers (64% female) from the Neurobiological Predictors of Huntington's Disease study were followed up for up to 12 y (mean = 5, standard deviation = 3.3) covering 2002 to 2014. No one had a motor diagnosis at study entry, but 225 (21%) carriers prospectively received a motor diagnosis. Analysis was performed with random survival forests, which is a machine learning method for right-censored data.ResultsAdding 34 variables along with cytosine-adenine-guanine and age substantially increased predictive accuracy relative to cytosine-adenine-guanine and age alone. Adding six of the common motor and cognitive variables (total motor score, diagnostic confidence level, Symbol Digit Modalities Test, three Stroop tests) resulted in lower predictive accuracy than the full set, but still had twice the 5-y predictive accuracy than when using cytosine-adenine-guanine and age alone. Additional analysis suggested interactions and nonlinear effects that were characterized in a post hoc Cox regression model.ConclusionsMeasurement of clinical variables can substantially increase the accuracy of predicting motor diagnosis over and above cytosine-adenine-guanine and age (and their interaction). Estimated probabilities can be used to characterize progression level and aid in future studies' sample selection.

Cognitive, motor and psychiatric changes in prodromal Huntington's disease have nurtured the emergent need for early interventions. Preventive clinical trials for Huntington's disease, however, are limited by a shortage of suitable measures that could serve as surrogate outcomes. Measures of intrinsic functional connectivity from resting-state functional magnetic resonance imaging are of keen interest. Yet recent studies suggest circumscribed abnormalities in resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease, despite the spectrum of behavioural changes preceding a manifest diagnosis. The present study used two complementary analytical approaches to examine whole-brain resting-state functional magnetic resonance imaging connectivity in prodromal Huntington's disease. Network topology was studied using graph theory and simple functional connectivity amongst brain regions was explored using the network-based statistic. Participants consisted of gene-negative controls (n = 16) and prodromal Huntington's disease individuals (n = 48) with various stages of disease progression to examine the influence of disease burden on intrinsic connectivity. Graph theory analyses showed that global network interconnectivity approximated a random network topology as proximity to diagnosis neared and this was associated with decreased connectivity amongst highly-connected rich-club network hubs, which integrate processing from diverse brain regions. However, functional segregation within the global network (average clustering) was preserved. Functional segregation was also largely maintained at the local level, except for the notable decrease in the diversity of anterior insula intermodular-interconnections (participation coefficient), irrespective of disease burden. In contrast, network-based statistic analyses revealed patterns of weakened frontostriatal connections and strengthened frontal-posterior connections that evolved as disease burden increased. These disturbances were often related to long-range connections involving peripheral nodes and interhemispheric connections. A strong association was found between weaker connectivity and decreased rich-club organization, indicating that whole-brain simple connectivity partially expressed disturbances in the communication of highly-connected hubs. However, network topology and network-based statistic connectivity metrics did not correlate with key markers of executive dysfunction (Stroop Test, Trail Making Test) in prodromal Huntington's disease, which instead were related to whole-brain connectivity disturbances in nodes (right inferior parietal, right thalamus, left anterior cingulate) that exhibited multiple aberrant connections and that mediate executive control. Altogether, our results show for the first time a largely disease burden-dependent functional reorganization of whole-brain networks in prodromal Huntington's disease. Both analytic approaches provided a unique window into brain reorganization that was not related to brain atrophy or motor symptoms. Longitudinal studies currently in progress will chart the course of functional changes to determine the most sensitive markers of disease progression.

ObjectiveAssessment of daily functions affected by cognitive loss in prodromal Huntington's disease (HD) is necessary in practice and clinical trials. We evaluated baseline and longitudinal sensitivity of the Everyday Cognition (ECog) scales in prodromal HD and compared self- and companion-ratings.MethodEveryday cognition was self-assessed by 850 participants with prodromal HD and 768 companions. We examined internal structure using confirmatory factor analysis (CFA) on baseline data. For longitudinal analysis, we stratified participants into Low, Medium, and High disease progression groups. We examined ECog scores for group differences and participant-and-companion differences using linear mixed effects regression (LMER). Comparison with the Total Functional Capacity (TFC) scale was made.ResultsCFA revealed good fit of a 5-factor model having a global factor (total score), and subfactors (subscales) of memory, language, visuospatial perception, and executive function. At study entry, participants and companions in the Medium and High groups reported significantly worsened everyday cognition as well as significant functional decline over time. Losses became more pronounced and participant and companion ratings diverged as individuals progressed. TFC showed significant functional loss over time in the High group but not in the Medium group.ConclusionsDisease progression is associated with reduced self- and companion-reported everyday cognition in prodromal HD participants who are less than 13 years to estimated motor onset. Our findings suggest companion ratings are more sensitive than participants' for detecting longitudinal change in daily cognitive function. ECog appears more sensitive to specific functional changes in the prodrome of HD than the TFC.

The current study sought to examine the utility of intra-individual variability (IIV) in distinguishing participants with prodromal Huntington disease (HD) from nongene-expanded controls. IIV across 15 neuropsychological tasks and within-task IIV using a self-paced timing task were compared as a single measure of processing speed (Symbol Digit Modalities Test [SDMT]) in 693 gene-expanded and 191 nongene-expanded participants from the PREDICT-HD study. After adjusting for depressive symptoms and motor functioning, individuals estimated to be closest to HD diagnosis displayed higher levels of across- and within-task variability when compared to controls and those prodromal HD participants far from disease onset (F ICV(3,877)=11.25; p

BackgroundAlthough the association between cytosine-adenine-guanine (CAG) repeat length and age at onset of Huntington's disease is well known, improved prediction of onset would be advantageous for clinical trial design and prognostic counselling. We compared various measures for tracking progression and predicting conversion to manifest Huntington's disease.MethodsIn this prospective observational study, we assessed the ability of 40 measures in five domains (motor, cognitive, psychiatric, functional, and imaging) to predict time to motor diagnosis of Huntington's disease, accounting for CAG repeat length, age, and the interaction of CAG repeat length and age. Eligible participants were individuals from the PREDICT-HD study (from 33 centres in six countries [USA, Canada, Germany, Australia, Spain, UK]) with the gene mutation for Huntington's disease but without a motor diagnosis (a rating below 4 on the diagnostic confidence level from the 15-item motor assessment of the Unified Huntington's Disease Rating Scale). Participants were followed up between September, 2002, and July, 2014. We used joint modelling of longitudinal and survival data to examine the extent to which baseline and change of measures analysed separately was predictive of CAG-adjusted age at motor diagnosis.Findings1078 individuals with a CAG expansion were included in this analysis. Participants were followed up for a mean of 5·1 years (SD 3·3, range 0·0-12·0). 225 (21%) of these participants received a motor diagnosis of Huntington's disease during the study. 37 of 40 cross-sectional and longitudinal clinical and imaging measures were significant predictors of motor diagnosis beyond CAG repeat length and age. The strongest predictors were in the motor, imaging, and cognitive domains: an increase of one SD in total motor score (motor domain) increased the risk of a motor diagnosis by 3·07 times (95% CI 2·26-4·16), a reduction of one SD in putamen volume (imaging domain) increased risk by 3·32 times (2·37-4·65), and a reduction of one SD in Stroop word score (cognitive domain) increased risk by 2·32 times (1·88-2·87).InterpretationPrediction of diagnosis of Huntington's disease can be improved beyond that obtained by CAG repeat length and age alone. Such knowledge about potential predictors of manifest Huntington's disease should inform discussions about guidelines for diagnosis, prognosis, and counselling, and might be useful in guiding the selection of participants and outcome measures for clinical trials.FundingUS National Institutes of Health, US National Institute of Neurological Disorders and Stroke, and CHDI Foundation.

Cognitive changes in the prodromal phase of Huntington disease (prHD) are found in multiple domains, yet their neural bases are not well understood. One component process that supports cognition is inhibitory control. In the present fMRI study, we examined brain circuits involved in response inhibition in 65 prHD participants and 36 gene-negative (NEG) controls using the stop signal task (SST). PrHD participants were subdivided into three groups (LOW, MEDIUM, HIGH) based on their CAG-Age Product (CAP) score, an index of genetic exposure and a proxy for expected time to diagnosis. Poorer response inhibition (stop signal duration) correlated with CAP scores. When response inhibition was successful, activation of the classic frontal inhibitory-network was normal in prHD, yet stepwise reductions in activation with proximity to diagnosis were found in the posterior ventral attention network (inferior parietal and temporal cortices). Failures in response inhibition in prHD were related to changes in inhibition centers (supplementary motor area (SMA)/anterior cingulate and inferior frontal cortex/insula) and ventral attention networks, where activation decreased with proximity to diagnosis. The LOW group showed evidence of early compensatory activation (hyperactivation) of right-hemisphere inhibition and attention reorienting centers, despite an absence of cortical atrophy or deficits on tests of executive functioning. Moreover, greater activation for failed than successful inhibitions in an ipsilateral motor-control network was found in the control group, whereas such differences were markedly attenuated in all prHD groups. The results were not related to changes in cortical volume and thickness, which did not differ among the groups. However, greater hypoactivation of classic right-hemisphere inhibition centers [inferior frontal gyrus (IFG)/insula, SMA/anterior cingulate cortex (ACC)] during inhibition failures correlated with greater globus pallidus atrophy. These results are the first to demonstrate that response inhibition in prHD is associated with altered functioning in brain networks that govern inhibition, attention, and motor control.

IntroductionThe brain mechanisms of cognitive impairment in prodromal Huntington disease (prHD) are not well understood. Although striatal atrophy correlates with some cognitive abilities, few studies of prHD have investigated whether cortical gray matter morphometry correlates in a regionally specific manner with functioning in different cognitive domains. This knowledge would inform the selection of cognitive measures for clinical trials that would be most sensitive to the target of a treatment intervention.MethodIn this study, random forest analysis was used to identify neuroanatomical correlates of functioning in five cognitive domains including attention and information processing speed, working memory, verbal learning and memory, negative emotion recognition, and temporal processing. Participants included 325 prHD individuals with varying levels of disease progression and 119 gene-negative controls with a family history of HD. In intermediate analyses, we identified brain regions that showed significant differences between the prHD and the control groups in cortical thickness and striatal volume. Brain morphometry in these regions was then correlated with cognitive functioning in each of the domains in the prHD group using random forest methods. We hypothesized that different regional patterns of brain morphometry would be associated with performances in distinct cognitive domains.ResultsThe results showed that performances in different cognitive domains that are vulnerable to decline in prHD were correlated with regionally specific patterns of cortical and striatal morphometry. Putamen and/or caudate volumes were top-ranked correlates of performance across all cognitive domains, as was cortical thickness in regions related to the processing demands of each domain.ConclusionsThe results underscore the importance of identifying structural magnetic resonance imaging (sMRI) markers of functioning in different cognitive domains, as their relative sensitivity depends on the extent to which processing is called upon by different brain networks. The findings have implications for identifying neuroimaging and cognitive outcome measures for use in clinical trials.

There is growing consensus that intervention and treatment of Huntington disease (HD) should occur at the earliest stage possible. Various early-intervention methods for this fatal neurodegenerative disease have been identified, but preventive clinical trials for HD are limited by a lack of knowledge of the natural history of the disease and a dearth of appropriate outcome measures. Objectives of the current study are to document the natural history of premanifest HD progression in the largest cohort ever studied and to develop a battery of imaging and clinical markers of premanifest HD progression that can be used as outcome measures in preventive clinical trials. Neurobiological predictors of Huntington's disease is a 32-site, international, observational study of premanifest HD, with annual examination of 1013 participants with premanifest HD and 301 gene-expansion negative controls between 2001 and 2012. Findings document 39 variables representing imaging, motor, cognitive, functional, and psychiatric domains, showing different rates of decline between premanifest HD and controls. Required sample size and models of premanifest HD are presented to inform future design of clinical and preclinical research. Preventive clinical trials in premanifest HD with participants who have a medium or high probability of motor onset are calculated to be as resource-effective as those conducted in diagnosed HD and could interrupt disease 7-12 years earlier. Methods and measures for preventive clinical trials in premanifest HD more than a dozen years from motor onset are also feasible. These findings represent the most thorough documentation of a clinical battery for experimental therapeutics in stages of premanifest HD, the time period for which effective intervention may provide the most positive possible outcome for patients and their families affected by this devastating disease.

BackgroundNeuroimaging studies suggest that volumetric MRI measures of specific brain structures may serve as excellent biomarkers in future clinical trials of Huntington disease (HD).ObjectiveDemonstration of the clinical significance of these measures is an important step in determining their appropriateness as potential outcome measures.MethodsMeasures of gray- and white-matter lobular volumes and subcortical volumes (caudate, putamen, globus pallidus, thalamus, nucleus accumbens, hippocampus) were obtained from MRI scans of 516 individuals who tested positive for the HD gene expansion, but were not yet exhibiting signs or symptoms severe enough to warrant diagnosis ("pre-HD"). MRI volumes (corrected for intracranial volume) were correlated with cognitive, motor, psychiatric, and functional measures known to be sensitive to subtle changes in pre-HD.ResultsCaudate, putamen, and globus pallidus volumes consistently correlated with cognitive and motor, but not psychiatric or functional measures in pre-HD. Volumes of white matter, nucleus accumbens, and thalamus, but not cortical gray matter, also correlated with some of the motor and cognitive measures.ConclusionsResults of regression analyses suggest that volumes of basal ganglia structures contributed more highly to the prediction of most motor and cognitive variables than volumes of other brain regions. These results support the use of volumetric measures, especially of the basal ganglia, as outcome measures in future clinical trials in pre-HD. Results may also assist investigators in selecting the most appropriate measures for treatment trials that target specific clinical features or regions of neuropathology.