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The Unified Huntington's Disease Rating Scale is used to characterize motor impairments and establish motor diagnosis. Little is known about the timing of diagnostic confidence level categories and the trajectory of motor impairments during the prodromal phase. Goals of this study were to estimate the timing of categories, model the prodromal trajectory of motor impairments, estimate the rate of motor impairment change by category, and provide required sample size estimates for a test of efficacy in clinical trials. In total, 1010 gene-expanded participants from the Neurobiological Predictors of Huntington's Disease (PREDICT-HD) trial were analyzed. Accelerated failure time models were used to predict the timing of categories. Linear mixed effects regression was used to model the longitudinal motor trajectories. Age and length of gene expansion were incorporated into all models. The timing of categories varied significantly by gene expansion, with faster progression associated with greater expansion. For the median expansion, the third diagnostic confidence level category was estimated to have a first occurrence 1.5 years before diagnosis, and the second and first categories were estimated to occur 6.75 years and 19.75 years before diagnosis, respectively. Motor impairments displayed a nonlinear prodromal course. The motor impairment rate of change increased as the diagnostic confidence level increased, with added acceleration for higher progression scores. Motor items can detect changes in motor impairments before diagnosis. Given a sufficiently high progression score, there is evidence that the diagnostic confidence level can be used for prodromal staging. Implications for Huntington's disease research and the planning of clinical trials of efficacy are discussed.

Huntington disease (HD) is a neurodegenerative disorder that involves preferential atrophy in the striatal complex and related subcortical nuclei. In this article, which is based on a dataset extracted from the PREDICT-HD study, we use statistical shape analysis with deformation markers obtained through "Large Deformation Diffeomorphic Metric Mapping" of cortical surfaces to highlight specific atrophy patterns in the caudate, putamen, and globus pallidus, at different prodromal stages of the disease. On the basis of the relation to cortico-basal ganglia circuitry, we propose that statistical shape analysis, along with other structural and functional imaging studies, may help expand our understanding of the brain circuitry affected and other aspects of the neurobiology of HD, and also guide the most effective strategies for intervention.

Neurocognitive disorders--including delirium, mild cognitive impairment and dementia--are characterized by decline from a previously attained level of cognitive functioning. These disorders have diverse clinical characteristics and aetiologies, with Alzheimer disease, cerebrovascular disease, Lewy body disease, frontotemporal degeneration, traumatic brain injury, infections, and alcohol abuse representing common causes. This diversity is reflected by the variety of approaches to classifying these disorders, with separate groups determining criteria for each disorder on the basis of aetiology. As a result, there is now an array of terms to describe cognitive syndromes, various definitions for the same syndrome, and often multiple criteria to determine a specific aetiology. The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) provides a common framework for the diagnosis of neurocognitive disorders, first by describing the main cognitive syndromes, and then defining criteria to delineate specific aetiological subtypes of mild and major neurocognitive disorders. The DSM-5 approach builds on the expectation that clinicians and research groups will welcome a common language to deal with the neurocognitive disorders. As the use of these criteria becomes more widespread, a common international classification for these disorders could emerge for the first time, thus promoting efficient communication among clinicians and researchers.

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 depen

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 resul

Subtle changes in motor function have been observed in individuals with prodromal Huntington disease (prHD), but the underlying neural mechanisms are not well understood nor is the cumulative effect of the disease (disease burden) on functional connectivity. The present study examined the resting-state functional magnetic resonance imaging (rs-fMRI) connectivity of the primary motor cortex (M1) in 16 gene-negative (NEG) controls and 48 gene-positive prHD participants with various levels of disease burden. The results showed that the strength of the left M1 connectivity with the ipsilateral M1 and somatosensory areas decreased as disease burden increased and correlated with motor symptoms. Weakened M1 connectivity within the motor areas was also associated with abnormalities in long-range connections that evolved with disease burden. In this study, M1 connectivity was decreased with visual centers (bilateral cuneus), but increased with a hub of the default mode network (DMN; posterior cingulate cortex). Changes in connectivity measures were associated with worse performance on measures of cognitive-motor functioning. Short- and long-range functional connectivity disturbances were also associated with volume loss in the basal ganglia, suggesting that weakened M1 connectivity is partly a manifestation of striatal atrophy. Altogether, the results indicate that the prodromal phase of HD is associated with abnormal interhemispheric interactions among motor areas and disturbances in the connectivity of M1 with visual centers and the DMN. These changes may, respectively, contribute to increased motor symptoms, visuomotor integration problems, and deficits in the executive control of movement as individuals approach a manifest diagnosis.

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.

BackgroundProdromal Huntington's disease (prHD) is associated with a myriad of cognitive changes but the domains that best predict time to clinical diagnosis have not been studied. This is a notable gap because some domains may be more sensitive to cognitive decline, which would inform clinical trials.ObjectivesThe present study sought to characterise cognitive domains underlying a large test battery and for the first time, evaluate their ability to predict time to diagnosis.MethodsParticipants included gene negative and gene positive prHD participants who were enrolled in the PREDICT-HD study. The CAG-age product (CAP) score was the measure of an individual's genetic signature. A factor analysis of 18 tests was performed to identify sets of measures or latent factors that elucidated core constructs of tests. Factor scores were then fit to a survival model to evaluate their ability to predict time to diagnosis.ResultsSix factors were identified: (1) speed/inhibition, (2) verbal working memory, (3) motor planning/speed, (4) attention-information integration, (5) sensory-perceptual processing and (6) verbal learning/memory. Factor scores were sensitive to worsening of cognitive functioning in prHD, typically more so than performances on individual tests comprising the factors. Only the motor planning/speed and sensory-perceptual processing factors predicted time to diagnosis, after controlling for CAP scores and motor symptoms. Conclusions The results suggest that motor planning/speed and sensory-perceptual processing are important markers of disease prognosis. The findings also have implications for using composite indices of cognition in preventive Huntington's disease trials where they may be more sensitive than individual tests.

We examined the Trail Making Test (TMT) in a sample of 767 participants with prodromal Huntington disease (prodromal HD) and 217 healthy comparisons to determine the contributions of motor, psychiatric, and cognitive changes to TMT scores. Eight traditional and derived TMT scores were also evaluated for their ability to differentiate prodromal participants closer to estimated age of diagnosis from those farther away and prodromal individuals from healthy comparisons. Results indicate that motor signs only mildly affected Part A, and psychiatric symptoms did not affect either part. Tests of perceptual processing, visual scanning, and attention were primarily associated with Part A, and executive functioning (response inhibition, set-shifting), processing speed, and working memory were associated with Part B. Additionally, TMT scores differentiated between healthy comparisons and prodromal HD individuals as far as 9-15 years before estimated diagnosis. In participants manifesting prodromal motor signs and psychiatric symptoms, the TMT primarily measures cognition and is able to discriminate between groups based on health status and estimated time to diagnosis.