Abstract
BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by the degeneration of both lower and upper motor neurons (UMN). Clinical heterogeneity manifests in subtypes such as bulbar-onset ALS (bALS) and spinal-onset ALS (sALS), with emerging evidence suggesting that oculomotor dysfunction may reflect broader multisystem involvement. This study aims to investigate oculomotor parameters across different ALS phenotypes and their associations with neuropsychological domains. METHODS: A total of 46 patients meeting the Gold Coast Criteria for ALS were enrolled, alongside 23 age- and education-matched healthy controls (HCs). Participants were assessed for demographic variables and clinical features, and underwent cognitive and oculomotor testing using the EyeKnow system. Eye movement performance was compared between groups, and correlations between oculomotor metrics and cognitive and clinical data were examined. RESULTS: ALS patients displayed longer reaction times in anti-saccade tasks (357.48 ± 61.28 ms vs. 316.10 ± 52.70 ms, p = 0.005) and significantly lower predictive saccade accuracy (86.77 ± 19.17% vs. 99.36 ± 2.22%, p < 0.001) compared to HCs. There is no significant difference in the eye movement parameters between sALS and bALS. Patients with bulbar involvement exhibited poorer performance in predictive saccade accuracy (77.53 ± 26.66% vs. 96.01 ± 4.92%, p < 0.001) and longer initial time in the smooth pursuit task (647.43 [402.14, 760.64] ms vs. 452.43 [131.62, 598.20] ms, U = 161.00, p = 0.037) compared to those without bulbar involvement. UMN involvement was associated with poorer performance across prosaccade, anti-saccade, and predictive saccade tasks. No significant correlation between oculomotor metrics and cognitive tests or clinical data was detected. CONCLUSIONS: The findings highlight the impact of bulbar and UMN involvement on oculomotor dysfunction in ALS, demonstrating distinct patterns across various phenotypes. Although oculomotor metrics show sensitivity to the pathophysiology of ALS, their effectiveness as independent biomarkers needs further validation through longitudinal studies that include larger cohorts, advanced neuroimaging techniques, and multimodal assessments to capture the complex interplay between motor, cognitive, and anatomical changes in this varied disease.