The use of quantitative oculometry in the assessment of Huntington’s disease

Huntington’s disease (HD) is a neurodegenerative disorder characterised by progressive motor, cognitive and psychiatric symptoms. Objective measurement of disease severity is of increasing importance for detecting symptomatic disease, as well as monitoring disease progression and the response to novel therapeutic interventions. Using a newly-developed infra-red scleral oculometer, we measured saccadic latencies and durations in HD patients exhibiting a broad range of symptoms (n=24) and control subjects of comparable ages (n=20) to see whether these parameters might reflect the presence or severity of HD. Latency distributions were characterised by creating reciprobit plots for each subject, whilst parametric statistics were applied to durations. Compared with the control group, we found the HD group had a significantly increased median latency, and early saccades were more prominent. In addition, HD patients exhibited an increased saccadic duration and variability of duration. Using Bayesian (likelihood) analysis, we obtained saccadic support values for the presence of clinical HD, which correlated with the motor Unified Huntington’s Disease Rating Scale (UHDRS) score in these patients. A sensitivity/specificity analysis of all 44 participants showed that the use of this multivariate support measure was highly successful in predicting HD status, correctly diagnosing 75% of the HD patients, and (95%) of the controls; with a different criterion, these figures were 96 and 15%. Furthermore, we correctly predicted absence of disease in two additional subjects subsequently confirmed to be genetically unaffected. This strongly suggests that multivariate support values derived from saccadic parameters may provide an objective, quantitative biomarker of HD, especially the degree of motor impairment. However, larger longitudinal studies are required to determine whether they can reliably detect the earliest presymptomatic disease, or faithfully reflect disease progression.