Background Prodromal 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.
Objectives The 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.
Methods Participants 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.
Results Six 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.
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Funding This research is supported by the National Institutes for Health, National Institute of Neurological Disorders and Stroke (NS40068) and CHDI Foundation Inc.
Competing interests None.
Ethics approval The study protocol was approved by the institutional review boards at the University of Iowa and participating sites.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement There are no unpublished data from the study. All PREDICT-HD data are shared on the NIH dbGaP website and can also be obtained from the PI at the University of Iowa and the corresponding author on this paper.