Objective:

To characterize domain-specific cognitive profiles across genetic subtypes of Parkinson’s disease (PD) using the Parkinson’s Progression Markers Initiative (PPMI) cohort and determine whether subtypes exhibit disproportionate memory, executive function, or visuospatial impairments.

Background:

Prior studies of genetic subtypes in PD have focused on global cognitive measures and biomarkers, leaving domain-specific neuropsychological patterns underexplored. These assessments may better detect subtype-related decline.

Design/Methods:

Participants were drawn from PPMI and stratified into three groups: (1) PD with pathogenic mutations (LRRK2 [n=127], GBA [n=73], SNCA [n=19], and PRKN [n=14]); (2) idiopathic PD without known mutations or risk variants (n=886); and (3) healthy controls (n=246). Participants were followed for three years. Neuropsychological assessments included the Benton Judgment of Line Orientation (BJLO), Hopkins Verbal Learning Test (HVLT), Letter-Number Sequencing (LNS), Semantic Fluency , and the Montreal Cognitive Assessment (MoCA). Baseline cognitive performance was compared using multivariate analysis of covariance (MANCOVA), adjusting for age at baseline, education, and disease duration. Longitudinal cognitive change was analyzed using repeated measures ANOVA. Statistical significance was defined as p<0.05.

Results:

At baseline, significant differences emerged across genetic subtypes on the BJLO, LNS, and HVLT Total Recall (all p < 0.05). SNCA carriers showed the lowest scores (BJLO 21.1, LNS 8.1, and HVLT 39.4; all p<0.05 vs other subtypes). No differences were observed for semantic fluency, HVLT recognition or retention, or MoCA. At three-year follow-up, repeated measures ANOVA showed significant group-by-time interactions for MoCA, Benton, HVLT Total Recall, and LNS (all p < 0.05), with SNCA exhibiting progressive decline relative to other subtypes (all p<0.05).

Conclusions:

Targeted neuropsychological assessments, particularly those measuring visuospatial ability, verbal memory, and executive function, can help identify individuals with elevated cognitive risk. These tools support more individualized clinical management strategies aimed at mitigating nonmotor disease burden.