Digital motor and cognitive variability as early markers of the prodromal Parkinson’s disease spectrum
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Background
Individuals with isolated REM sleep behaviour disorder (iRBD) show motor and cognitive dysfunction prior to clinical α-synucleinopathy. Performance instability may represent an earlier marker of neurodegeneration but remains underexplored using digital tests.
Objectives
To assess baseline and longitudinal differences in motor and cognitive performance and examine performance variability in iRBD and related phenotypes.
Methods
Three PD-risk-stratified prodromal cohorts (normosmic probable RBD (pRBD), hyposmic pRBD and polysomnography-confirmed iRBD (PSG-iRBD)) were compared with healthy controls. Participants completed the BRadykinesia Akinesia Incoordination (BRAIN) test, Distal Finger Tapping (DFT) test, and Trail Making Test (TMT) remotely. Motor outcomes included kinesia score (KS), akinesia time (AT), and incoordination score (IS); cognitive outcomes included TMT-A/B reaction times and executive function. Baseline differences were analysed using age- and sex-adjusted logistic regression, longitudinal change using linear mixed-effects models, and variability using the mean of squared successive differences (MSSD) and heteroscedastic modelling.
Results
At baseline, PSG-iRBD participants showed greater motor and cognitive impairment than controls, hyposmic pRBD demonstrated intermediate deficits and normosmic pRBD participants showed milder but significant impairments. Linear mixed-effects models showed no change in motor trajectories across all groups, while executive function declined significantly in PSG-iRBD (p=0.001). However, variance modelling showed widespread variability. Cognitive variability was elevated in PSG-iRBD and hyposmic pRBD participants (MSSD p<0.035), and heteroscedastic modelling captured significant visit-specific motor instability across all prodromal cohorts on the BRAIN test (all p<0.02).
Conclusions
Performance variability precedes measurable linear decline across PD-risk stratified groups. Remote digital testing offers a scalable framework to capture this early instability.
