Background
Methods to detect early cognitive decline and account for heterogeneity of deficits in Parkinson's disease (PD) are needed. Quantitative methods such as latent class analysis (LCA) offer an objective approach to delineate discrete phenotypes of impairment.
Objective
To identify discrete neurocognitive phenotypes in PD patients without dementia.
Methods
LCA was applied to a battery of 8 neuropsychological measures to identify cognitive subtypes in a cohort of 199 non-demented PD patients. Two measures were analyzed from each of four neurocognitive domains: executive functioning, memory, visuospatial abilities, and language. Additional analyses examined between-groups differences in demographic and clinical characteristics (Alzheimer's Disease Cooperative Study Activities of Daily Living Inventory [ADCS-ADL]; UPDRS-III; PD subtype (i.e., tremor-dominant (TD) versus postural instability/gait disturbance-dominant(PIGD)); and cognitive diagnosis (i.e., intact cognition versus mild cognitive impairment; MCI).
Results
LCA identified 3 distinct groups of PD patients: an intact cognition group (n=109; 54.8%), an amnestic group (n=64[32.1%]; impaired recall and recognition on verbal memory tasks, but intact performance on other measures) and a mixed impairment group with dysexecutive, visuospatial and lexical retrieval deficits (n=26 [13.1%]; relative deficits on measures of verbal fluency, visuospatial abilities, and delayed free recall on a memory task, but intact recognition memory). The amnestic and mixed impairment groups had significantly lower ratings of IADL functioning and greater motor symptoms than the cognitively intact group. Additionally, patients with PIGD vs. TD PD subtype were more likely to be classified in either cognitively impaired group. Of those diagnosed as cognitively normal according to MDS criteria (n=151), LCA classified 35 patients as amnestic (23.2%), and 15 as mixed impairment (9.9%).
Conclusions
Non-demented PD patients exhibit distinct neuropsychological profiles. One-third of patients with LCA-determined impairment were diagnosed as cognitively intact by expert consensus, indicating that classification using a statistical algorithm may assist in detection of early and subtle cognitive decline. This study also demonstrates that memory impairment is common in non-demented PD even when cognitive impairment is not clinically apparent. This study has implications for earlier detection of cognitive difficulties in PD, predicting eventual emergence of significant cognitive decline, and treatment trials for cognitive dysfunction in PD.