Unified Huntington's disease rating scale: Reliability and consistency

Kieburtz, Karl; Penney, John B.; Corno, Peter; Ranen, Neal G.; Shoulson, Ira; Feigin, Andrew; Abwender, David A.; Greenarnyre, J. Timothy; Higgins, Donald S.; Marshall, Frederick J.; Goldstein, Joshua; Steinberg, Kimberly; Shih, Charles C.-Y.; Richard, Irene Hegeman; Hickey, Charlyne; Zimmerman, Carol; Orme, Constance; Claude, Kathy; Oakes, David; Sax, Daniel S.; Kim, Anthony; Hersch, Steven M.; Jones, Randi; Auchus, Alexander P.; Olsen, David; Bissey-Black, Cheryl; Rubin, Allen; Schwartz, Rose; Dubinsky, Richard; Mallonee, William M.; Gray, Carolyn Steele; Godfrey, Nan; Suter, Greg; Shannon, Kathleen M.; Stebbins, Glenn T.; Jaglin, Jean A.; Marder, Karen; Taylor, Stuart P.; Louis, Elan D.; Moskowitz, Carol; Thorne, Deborah Z.; Zubin, Naomi; Wexler, Nancy S.; Swenson, Michael R.; Paulsen, Jane S.; Swerdlow, Neal R.; Albin, Roger L.; Wernette, Christine; Walker, Francis O.; Hunt, Vicki

doi:10.1002/mds.870110204

Cited by 1,763 publications

(555 citation statements)

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“…Here, we use the Total Motor Score (TMS),21 Symbol Digit Modalities Test (SDMT),22 Stroop test, and scaled CAG‐age‐product (CAP)23 as widely used markers of disease‐driven motor, cognitive, and genetic onset, respectively. These markers are used to validate the staging under the hypothesis that a subject with a high EBM stage will have poor motor and cognitive scores.…”

Section: Methodsmentioning

confidence: 99%

An image‐based model of brain volume biomarker changes in Huntington's disease

Wijeratne

Young

Oxtoby

et al. 2018

Ann Clin Transl Neurol

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ObjectiveDetermining the sequence in which Huntington's disease biomarkers become abnormal can provide important insights into the disease progression and a quantitative tool for patient stratification. Here, we construct and present a uniquely fine‐grained model of temporal progression of Huntington's disease from premanifest through to manifest stages.MethodsWe employ a probabilistic event‐based model to determine the sequence of appearance of atrophy in brain volumes, learned from structural MRI in the Track‐HD study, as well as to estimate the uncertainty in the ordering. We use longitudinal and phenotypic data to demonstrate the utility of the patient staging system that the resulting model provides.ResultsThe model recovers the following order of detectable changes in brain region volumes: putamen, caudate, pallidum, insula white matter, nonventricular cerebrospinal fluid, amygdala, optic chiasm, third ventricle, posterior insula, and basal forebrain. This ordering is mostly preserved even under cross‐validation of the uncertainty in the event sequence. Longitudinal analysis performed using 6 years of follow‐up data from baseline confirms efficacy of the model, as subjects consistently move to later stages with time, and significant correlations are observed between the estimated stages and nonimaging phenotypic markers.InterpretationWe used a data‐driven method to provide new insight into Huntington's disease progression as well as new power to stage and predict conversion. Our results highlight the potential of disease progression models, such as the event‐based model, to provide new insight into Huntington's disease progression and to support fine‐grained patient stratification for future precision medicine in Huntington's disease.

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Section: Methodsmentioning

confidence: 99%

An image‐based model of brain volume biomarker changes in Huntington's disease

Wijeratne

Young

Oxtoby

et al. 2018

Ann Clin Transl Neurol

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“…Gene mutation was determined by way of the extended number of CAG triplets on the huntingtin gene. Subjects were divided into four groups according to their UHDRS motor score (Huntington Study Group, 1996) and groups cutoffs according to Andrich et al. (2002): presymptomatic HD (PHD) subjects, score 0–4; early symptomatic HD patients (EHD), score 6–23; midsymptomatic HD patients (MHD), score 25–41; and late symptomatic HD patients (LHD), score 53–88.…”

Section: Methodsmentioning

confidence: 99%

Evidence of cardiac electrical remodeling in patients with Huntington disease

et al. 2018

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ObjectiveAlthough Huntington's disease (HD) is a disease of the central nervous system, HD mortality surveys indicate heart disease as a major cause of death. Cardiac dysfunction in HD might be a primary consequence of peripherally expressed mutant huntingtin or secondary to either a general decline in health or the onset of neurological dysfunction. The aim of the study was to clarify the heart muscle involvement.Materials and MethodsWe measured conventional and advanced resting ECG indices. Thirtyone subjects with a confirmed huntingtin gene mutation and 31 age‐ and gender‐matched controls were included. The HD subjects were divided into four groups based on their Unified Huntington Disease Rating Scale (UHDRS) motor score.ResultsWe detected changes in advanced ECG variables connected with electrical ventricular remodeling (t test, p < 0.01). The increase in the unexplained part of both QT variability and the standard deviation of normal‐to‐normal QT intervals, presumably reflecting beat‐to‐beat changes in repolarization, was most pronounced. Further, both variables correlated with the product of the cytosine–adenine–guanine (CAG) triplets’ repeat length and the subjects’ age (CAP), the former R = 0.423 (p = 0.018) and the latter R = 0.499 (p = 0.004). There was no correlation between the CAP score and any of variables representing autonomic nervous system activity.ConclusionsBoth autonomic nervous system dysfunction and cardiac electrical remodeling are present in patients with HD. The changes in advanced ECG variables observed in the study evolve with HD progression. The increased values of QT unexplained variability may be a marker of temporal inhomogeneity in ventricular repolarization associated with malignant ventricular arrhythmias.

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“…These individuals were submitted to imaging studies and clinical evaluations, which included the Unified Huntington's Disease Rating Scale -motor part, validated to the Portuguese language 12,13 ; the Mini Mental State Examination…”

Section: Methodsmentioning

confidence: 99%

Diffusion tensor imaging of brain white matter in Huntington gene mutation individuals

Saba

Yared

Doring³

et al. 2017

Arq. Neuro-Psiquiatr.

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Objective: To evaluate the role of the involvement of white matter tracts in huntingtin gene mutation patients as a potential biomarker of the progression of the disease. Methods: We evaluated 34 participants (11 symptomatic huntingtin gene mutation, 12 presymptomatic huntingtin gene mutation, and 11 controls). We performed brain magnetic resonance imaging to assess white matter integrity using diffusion tensor imaging, with measurement of fractional anisotropy. Results: We observed a significant decrease of fractional anisotropy in the cortical spinal tracts, corona radiate, corpus callosum, external capsule, thalamic radiations, superior and inferior longitudinal fasciculus, and inferior frontal-occipital fasciculus in the Huntington disease group compared to the control and presymptomatic groups. Reduction of fractional anisotropy is indicative of a degenerative process and axonal loss. There was no statistically significant difference between the presymptomatic and control groups. Conclusion: White matter integrity is affected in huntingtin gene mutation symptomatic individuals, but other studies with larger samples are required to assess its usefulness in the progression of the neurodegenerative process.

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Unified Huntington's disease rating scale: Reliability and consistency

Cited by 1,763 publications

References 10 publications

An image‐based model of brain volume biomarker changes in Huntington's disease

An image‐based model of brain volume biomarker changes in Huntington's disease

Evidence of cardiac electrical remodeling in patients with Huntington disease

Diffusion tensor imaging of brain white matter in Huntington gene mutation individuals

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