J01 Improving Prediction Of Huntington Disease Onset With Clinical And Imaging Measures: A 10-year Preopective Study Of Converters. (17th September 2014)

• Record Type: Journal Article
• Authors: Paulsen, J; Long, JD; Ross, C; Harrington, D; Erwin, C; Williams, J; Westervelt, H; Johnson, H; Aylward, E; Zhang, Y; Bockholt, J; Barker, R
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 85(2014)Supplement 1
• Page Start: A65
• Page End: A65
• Publication Date: 2014-09-17
• Subjects: Prediction -- diagnosis -- onset -- HD -- premanifest; Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2014-309032.184
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Background: Although correlation between CAG repeat length and age of HD onset is well known, improved prediction of onset would be advantageous for clinical trial sample enrichment and genetic counselling. Aims: To examine the predictive utility of genetic, demographic, motor, cognitive, psychiatric, functional and imaging measures for predicting conversion to manifest HD. Methods: Over 1000 research participants with the gene mutation for HD from 33 worldwide sites were followed for up to 10 years (average=6; range 1–10). A subset of 211 participants prospectively converted to manifest HD according to standard motor criteria. Results: The association between CAG repeats and onset age was replicated using a prospectively diagnosed cohort. Further, cross-sectional and longitudinal clinical and imaging measures were highly predictive of motor diagnosis beyond CAG repeat length and age. For example, a one standard deviation (SD) difference in total motor score increased the likelihood of motor diagnosis by 3X6 times, one SD loss in putamen volume by 2X9 times and one SD cognitive decline 2X2 times. Conclusions: Prediction of HD onset can considerably improve above and beyond that obtained by CAG repeat length and age alone. Many of the measures shown are inexpensive and efficient and could readily be integrated into clinical care at bedside, the clinic, or in the field. Refined predictors of onset can provide evidence for revised diagnostic guidelines and may be utilised for prognostic counselling. Prediction models can be used for enrichment of clinical trial samples and predictors can more precisely determine covariates to reduce costs of clinical trials. Funding: National Institutes for Health, National Institute of Neurological Disorders and Stroke 040068, and CHDI Foundation, Inc.