Objective: To evaluate whether a composite oculomotor index integrating multiple eye movement domains improves discrimination between PD and MSA.

Background: Differentiating Parkinson’s disease (PD) from multiple system atrophy (MSA) remains difficult, particularly in early disease stages. Oculomotor abnormalities occur in both disorders, but individual parameters often show limited diagnostic value.

Method: Oculomotor recordings from memory-guided saccades, antisaccades and smooth pursuit tasks were analyzed in patients with PD and MSA. The exploratory cohort included 22 PD and 17 MSA patients after clinical mapping. Based on biologically motivated hypotheses, a composite index was constructed using three prespecified parameters: memory saccade latency, number of correct antisaccades and smooth pursuit speed variability. Variables were winsorized (5–95 percentile), standardized and combined into a single score, where higher values indicated a more MSA-like profile. Group differences were assessed using the Mann–Whitney test and diagnostic performance using ROC analysis.

Results: Complete-case analysis included 14 PD and 13 MSA patients. The composite index significantly differentiated PD and MSA (median −0.499 vs 0.129; p=0.0061). Diagnostic performance was good, with an AUC of 0.81 (95% CI 0.63–0.96). Individual parameters showed consistent but weaker trends, including longer memory saccade latency, fewer correct antisaccades and altered pursuit dynamics in MSA.

Conclusion: A composite oculomotor biomarker integrating memory saccade latency, inhibitory control and smooth pursuit variability differentiated PD from MSA in this exploratory cohort. Combined eye movement measures may represent a promising physiological biomarker for the differential diagnosis of parkinsonian syndromes.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/a-composite-oculomotor-biomarker-for-differentiating-parkinsons-disease-from-multiple-system-atrophy/