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Prediction of manifest Huntington’s disease with clinical and imaging measures: a prospective observational study


Paulsen, Jane S., Long, Jeffrey D, Ross, Christopher A, Harrington, Deborah L, Erwin, Cheryl J, Williams, Janet K, Westervelt, Holly James, Johnson, Hans J, Aylward, Elizabeth H, Zhang, Ying, Bockholt, H Jeremy, Barker, Roger A


The Lancet. Neurology, Volume: 13, No.: 12, Pages.: 1193-1201

Year of Publication



Background: Although 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.; Methods: In 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.; Findings: 1078 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).; Interpretation: Prediction 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.; Funding: US National Institutes of Health, US National Institute of Neurological Disorders and Stroke, and CHDI Foundation.; Copyright © 2014 Elsevier Ltd. All rights reserved.

Bibtex Citation

@article{Paulsen_2014, doi = {10.1016/s1474-4422(14)70238-8}, url = {}, year = 2014, month = {dec}, publisher = {Elsevier {BV}}, volume = {13}, number = {12}, pages = {1193--1201}, author = {Jane S Paulsen and Jeffrey D Long and Christopher A Ross and Deborah L Harrington and Cheryl J Erwin and Janet K Williams and Holly James Westervelt and Hans J Johnson and Elizabeth H Aylward and Ying Zhang and H Jeremy Bockholt and Roger A Barker}, title = {Prediction of manifest Huntington{textquotesingle}s disease with clinical and imaging measures: a prospective observational study}, journal = {The Lancet Neurology} }


adult, aged, aged, 80 and over, diagnosis, diagnostic imaging, epidemiology, female, genetics, humans, huntington disease, huntingtons, longitudinal studies, male, middle aged, prediction, predictive value of tests, prospective studies, symptoms, trends

Countries of Study


Types of Dementia


Types of Study

Instrument development and testing (cross walking of measures, etc.)

Type of Interventions

Diagnostic Target Identification

Diagnostic Targets

Biological Testing, Cognition testing (inc. task driven tests such as clock drawing), Neuroimaging (e.g. MRI, PET, CAT etc.)