To develop a novel eye-movement based quantitative paradigm to diagnose and monitor progression of Huntington’s disease (HD).

There is no quantitative biomarker for HD. Clinical diagnosis of HD relies on neurological assessment of motor and cognitive ability, including eye movements. Altered saccadic and pursuit eye movements may be valuable in detecting early motor disease and conducting differential diagnosis. Quantitative eye-movement analysis thus offers a promising paradigm for objective diagnosis of HD.

We used a low-cost and portable eye-tracking system, with a customized visuomotor battery and analysis software to measure and characterize eye movements in 25 participants (10 early symptomatic HD, 10 with prodromal HD, and 5 healthy controls). Neurological and neuro-ophthalmological examination was also performed. We conducted and recorded visuomotor tests consisting of pursuits, fixation, and saccadic tasks. Machine learning algorithms were used for disease state classification, and a model-based quantitative composite oculomotor score was derived from eye-movement data of each participant.