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Lancet Neurol. 2014 Dec;13(12):1193-201. doi: 10.1016/S1474-4422(14)70238-8. Epub 2014 Nov 3.

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

Author information

1
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Neurology, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Psychology, University of Iowa, Iowa City, IA, USA. Electronic address: predict-publications@uiowa.edu.
2
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, IA, USA.
3
Division of Neurobiology, Departments of Psychiatry, Neurology, Neuroscience and Pharmacology, Johns Hopkins University, Baltimore, MD, USA.
4
Department of Radiology, School of Medicine, University of California, San Diego, CA, USA; Veterans Affairs San Diego Healthcare System, San Diego, CA, USA.
5
Center of Excellence for Ethics, Humanities & Spirituality, Texas Tech University Health Sciences Center, School of Medicine, Lubbock, TX, USA.
6
College of Nursing, University of Iowa, Iowa City, IA, USA.
7
Department of Psychiatry and Human Behavior, Division of Biology and Medicine, Alpert Medical School, Brown University, Providence, RI, USA; Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA.
8
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Departments of Electrical and Computer Engineering and Biomedical Engineering, College of Engineering, University of Iowa, Iowa City, IA, USA.
9
Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA, USA.
10
Department of Biostatistics, Fairbanks School of Public Health, and Indiana University School of Medicine, Indiana University, Indianapolis, IN, USA.
11
Advanced Biomedical Informatics Group, Iowa City, IA, USA.
12
Department of Clinical Neurosciences, John van Geest Centre for Brain Repair, University of Cambridge, Cambridge, UK.

Abstract

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.

Comment in

PMID:
25453459
PMCID:
PMC4373455
DOI:
10.1016/S1474-4422(14)70238-8
[Indexed for MEDLINE]
Free PMC Article

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