Latent Cognitive Phenotypes in De Novo Parkinson's Disease: A Person-Centered Approach

Systematic review of data-driven cognitive subtypes in Parkinson disease

BACKGROUND AND PURPOSE

Recent application of the mild cognitive impairment concept to Parkinson disease (PD) has proven valuable in identifying patients at risk of dementia. However, it has sparked controversy regarding the existence of cognitive subtypes. The present review evaluates the current literature pertaining to data-driven subtypes of cognition in PD.

METHODS

Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, systematic literature searches for peer-reviewed articles on the topic of cognitive subtyping in PD were performed.

RESULTS

Twenty-two relevant articles were identified in the systematic search. Subtype structures showed either a spectrum of severity or specific domains of impairment. Domain-specific subtypes included amnestic/nonamnestic, memory/executive, and frontal/posterior dichotomies, as well as more complex structures with less definitive groupings. Preliminary longitudinal evidence showed some differences in cognitive progression among subtypes. Neuroimaging evidence provided insight into distinct patterns of brain alterations among subtypes.

CONCLUSIONS

Recurring phenotypes in the literature suggest strong clinical relevance of certain cognitive subtypes in PD. Although the current literature is limited, it raises critical questions about the utility of data-driven methods in cognitive research. The results encourage further integration of neuroimaging research to define the latent neural mechanisms behind divergent subtypes. Although there is no consensus, there appears to be growing consistency and inherent value in identifying cognitive subtypes in PD.

Heterogenous Subtypes of Late-Life Depression and Their Cognitive Patterns: A Latent Class Analysis

Background

Late-life depression (LLD), characterized by cognitive deficits, is considered heterogeneous across individuals. Previous studies have identified subtypes with diverse symptom profiles, but their cognitive patterns are unknown. This study aimed to investigate the subtypes of LLD and the cognitive profile of each group.

Methods

In total, 109 depressed older adults were enrolled. We performed latent class analysis using Geriatric Depression Scale items as indicators to generate latent classes. We compared the sociodemographic and clinical characteristics with cognitive functions between groups and conducted regression analysis to investigate the association between class membership and variables with significant differences.

Results

Two classes were identified: the "pessimistic" group was characterized by pessimistic thoughts and the "worried" group with a relatively high prevalence of worry symptoms. The two groups did not differ in sociodemographic characteristics. The "pessimistic" group showed a higher rate of past history of depression and lower age of onset. The "worried" group had more physical comorbidities and a higher rate of past history of anxiety. The "pessimistic" group was more impaired in general cognitive function, executive function, information processing speed, and attention. Lower general and executive functions were associated with the membership in the "pessimistic" group.

Conclusions

Subjects with pessimistic symptoms and subjects with a propensity to worry may form two distinct subtypes of late-life depression with different cognitive profiles. Further, the cognitive evaluation of subjects with pessimistic symptoms is of utmost importance.

Montreal Cognitive Assessment: Seeking a Single Cutoff Score May Not Be Optimal

Background

Cutoff scores of the Montreal cognitive assessment (MoCA) for screening mild cognitive impairment in older adults differ across the world and within the Chinese culture. It is argued that to seek a cutoff score is essential to classify test participants. It was unknown how taking a classifying approach might reveal the cutoff score for identifying mildly cognitively impaired older adults.

Methods

Participants, selected from 13 communities in Wuhan, China, were tested with the Chinese version of MoCA and rated with the Activities of Daily Living and the Clinical Dementia Rating scales. Mixture modeling was applied to the data with certain covariates and MoCA sum scores as the outcome of the latent class. Models with different numbers of classes were compared in terms of information criteria, likelihood ratio test, entropy, and interpretability.

Results

A 3-class model (normal, mildly impaired, and severely impaired) was found to fit the data best. The normal class averaged a MoCA score of 24, while the severely impaired class averaged a score below 18. For those cases with MoCA scores above 18 and below 24, it is not certain if they are in the normal or the severely impaired classes.

Conclusion

Latent variable classification modeling provides another option to identify MCI in older adults. Some categorically different cases of MCI cannot be captured with any single MoCA sum score. A range of 18–24 MoCA scores might serve as a better screening criterion of MCI. Older adults who scored within this gray zone should be monitored for potential interventions.

Cognitive Decline in Parkinson's Disease: A Subgroup of Extreme Decliners Revealed by a Data-Driven Analysis of Longitudinal Progression

Cognitive impairment is an important symptom of Parkinson’s disease (PD) and predicting future cognitive decline is crucial for clinical practice. Here, we aim to identify latent sub-groups of longitudinal trajectories of cognitive change in PD patients, and explore predictors of differences in cognitive change. Longitudinal cognitive performance data from 349 newly diagnosed PD patients and 145 healthy controls from the Parkinson Progression Marker Initiative were modeled using a multivariate latent class linear mixed model. Resultant latent classes were compared on a number of baseline demographics and clinical variables, as well as cerebrospinal fluid (CSF) biomarkers and striatal dopamine transporter (DAT) density markers of neuropathology. Trajectories of cognitive change in PD were best described by two latent classes. A large subgroup (90%), which showed a subtle impairment in cognitive performance compared to controls but remained stable over the course of the study, and a small subgroup (10%) which rapidly declined in all cognitive performance measures. Rapid decliners did not differ significantly from the larger group in terms of disease duration, severity, or motor symptoms at baseline. However, rapid decliners had lower CSF amyloidß42 levels, a higher prevalence of sleep disorder and pronounced loss of caudate DAT density at baseline. These data suggest the existence of a distinct minority sub-type of PD in which rapid cognitive change in PD can occur uncoupled from motor symptoms or disease severity, likely reflecting early pathological change that extends from motor areas of the striatum into associative compartments and cortex.

Profile of social self-management practices in daily life with Parkinson's disease is associated with symptom severity and health quality of life

Purpose: Social participation is a key determinant of healthy aging, yet little is known about how people with Parkinson's disease manage social living. This study describes individual differences in social self-management practices and their association with symptom severity and health quality of life.Methods: People with Parkinson's disease (N = 90) completed measures of healthy routines, activities and relationships, symptom severity, and health related quality of life. Cluster analysis identified profiles of social self-management practices. Analysis of variance tested differences between profiles in symptom severity and health quality of life.Results: Participants clustered into one of seven groups according to different combinations of three practices: health resources utilization, activities in home and community, and social support relationships. The healthiest cluster engaged equally in all three practices at above sample average degree of engagement. Four clusters that engaged at or above sample average in activities in home and community experienced less health problems than three clusters that engaged below average. Variation in aspects of social lifestyle unrelated to health appeared also to contribute to profile diversity.Conclusion: Findings provide insight into similarity and variation in how people with Parkinson's disease engage with social self-management resources and point to person-centered interventions.Implications for RehabilitationSocial self-management is a biopsychosocial construct to identify and describe self-care practices that engage one's social resources for managing healthful daily living.People with Parkinson's disease vary in their profiles of engaging in social self-management practices in daily living, and this variability relates to severity of symptoms and health quality of life.Learning how to identify health-centered social self-management practices may help people with Parkinson's disease to focus on the healthfulness of their own practices.Learning how to strategically engage one's social resources as part of self-care may help people with Parkinson's disease to master managing their health and well-being in daily life.

Neural correlates of distinct cognitive phenotypes in early Parkinson's disease

OBJECTIVE

Cognitive decline is common in Parkinson's disease (PD), but changes can occur in a variety of cognitive domains. The lack of a single cognitive phenotype complicates diagnosis and tracking. In an earlier study we used a data-driven approach to identify distinct cognitive phenotypes of early PD. Here we identify the morphometric brain differences between those different phenotypes compared with cognitively normal PD participants.

METHODS

Six different cognitive classes were included (Weak, Typical, Weak-Visuospatial/Strong-Memory, Weak-Visuospatial, Amnestic, Strong). Structural differences between each class and the Typical class were assessed by deformation-based morphometry.

RESULTS

The different groups evidenced different patterns of atrophy. Weak class had frontotemporal and insular atrophy; Weak-Visuospatial/Strong-Memory class had frontotemporal, insular, parietal, and putamen atrophy; Weak-Visuospatial class had Rolandic operculum; Amnestic class had left frontotemporal, occipital, parietal and insular atrophy when compared to the Typical class. The Strong class did not have any atrophy but had significant differences in left temporal cortex in comparison to the Typical class.

CONCLUSIONS

Structural neuroimaging differences are evident in PD patients with distinct cognitive phenotypes even very early in the disease process prior to the emergence of frank cognitive impairment. Future studies will elucidate whether these have prognostic value in identifying trajectories toward dementia, or if they represent groups sensitive to different treatments.

Cognitive Performance in Parkinson's Disease in the Brain Health Registry

The study of cognition in Parkinson's disease (PD) traditionally requires exhaustive recruitment strategies. The current study examines data collected by the Brain Health Registry (BHR) to determine whether ongoing efforts to improve the recruitment base for therapeutic trials in Alzheimer's disease may be similarly effective for PD research, and whether online cognitive measurements can discriminate between participants who do and do not report a PD diagnosis. Participants enrolled in the BHR (age ≥50) with self-reported PD data and online cognitive testing available were included (n = 11,813). Associations between baseline cognitive variables and diagnostic group were analyzed using logistic regression. Linear mixed effects models were used to analyze longitudinal data. A total of 634 participants reported PD diagnosis at baseline with no self-reported cognitive impairment and completed cognitive testing. Measures of visual learning and memory, processing speed, attention, and working memory discriminated between self-reported PD and non-PD participants after correcting for multiple comparisons (p values < 0.006). Scores on all cognitive tests improved over time in PD and controls with the exception of processing speed, which remained stable in participants with PD while improving in those without. We demonstrate that a novel online approach to recruitment and longitudinal follow-up of study participants is effective for those with self-reported PD, and that significant differences exist between those with and without a reported diagnosis of PD on computerized cognitive measures. These results have important implications for recruitment of participants with PD into targeted therapeutic trials or large-scale genetic and cognitive studies.