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. 2024 Jul:124:107016.
doi: 10.1016/j.parkreldis.2024.107016. Epub 2024 May 22.

Replication and reliability of Parkinson's disease clinical subtypes

Therese V Cash  1 , Christina N Lessov-Schlaggar  2 , Erin R Foster  3 , Peter S Myers  1 , Joshua J Jackson  4 , Baijayanta Maiti  5 , Paul T Kotzbauer  1 , Joel S Perlmutter  6 , Meghan C Campbell  7
Affiliations

Replication and reliability of Parkinson's disease clinical subtypes

Therese V Cash et al. Parkinsonism Relat Disord. 2024 Jul.

Abstract

Background: We recently identified three distinct Parkinson's disease subtypes: "motor only" (predominant motor deficits with intact cognition and psychiatric function); "psychiatric & motor" (prominent psychiatric symptoms and moderate motor deficits); "cognitive & motor" (cognitive and motor deficits).

Objective: We used an independent cohort to replicate and assess reliability of these Parkinson's disease subtypes.

Methods: We tested our original subtype classification with an independent cohort (N = 100) of Parkinson's disease participants without dementia and the same comprehensive evaluations assessing motor, cognitive, and psychiatric function. Next, we combined the original (N = 162) and replication (N = 100) datasets to test the classification model with the full combined dataset (N = 262). We also generated 10 random split-half samples of the combined dataset to establish the reliability of the subtype classifications. Latent class analyses were applied to the replication, combined, and split-half samples to determine subtype classification.

Results: First, LCA supported the three-class solution - Motor Only, Psychiatric & Motor, and Cognitive & Motor- in the replication sample. Next, using the larger, combined sample, LCA again supported the three subtype groups, with the emergence of a potential fourth group defined by more severe motor deficits. Finally, split-half analyses showed that the three-class model also had the best fit in 13/20 (65%) split-half samples; two-class and four-class solutions provided the best model fit in five (25%) and two (10%) split-half replications, respectively.

Conclusions: These results support the reproducibility and reliability of the Parkinson's disease behavioral subtypes of motor only, psychiatric & motor, and cognitive & motor groups.

Keywords: Classification; Latent class analysis; Parkinson disease; Psychometrics.

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Conflict of interest statement

Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests. Therese Cash received support from NIH (NS097437, NS075321, NS097799, NS124738, NS118146, AT011015). Christina N. Lessov-Schlaggar received support from NINDS NS097437. Erin R. Foster is funded by the National Institutes of Health (NIA R21AG063974, NIA R01AG065214, NIDDK R01DK126826, R01DK064832), the American Parkinson Disease Association (APDA) (ID# 971,949), and the APDA Advanced Parkinson Disease Research Center at Washington University in St Louis, and the Missouri Chapter of the APDA. Peter S. Myers received support from NINDS NS097437. Joshua J. Jackson received support from NINDS NS097437, NIMH AG061162-01, NIDCD DC017522-02S1. Baijayanta Maiti received funding from NINDS K23 NS125107, National Center for Advancing Translational Sciences of the National Institute of Health KL2 TR002346, American Academy of Neurology and American Brain Foundation Clinical Research Training Fellowship in Parkinson's disease, Parkinson Study Group/Parkinson's Disease Foundation Mentored Clinical Research Award, Missouri Chapter of American Parkinson Disease Association, and the Jo Oertli fund and has received honoraria for reviewing grants as a member of the Parkinson Study Group mentoring committee and from the American Academy of Neurology for authorship. Paul T. Kotzbauer received funding from National Institutes of Health NS110436, NS097799, NS075321, NS110456, AG071754, NS123860, NS097437, and from Biogen and has received previous funding and honoraria from AbbVie. Joel S. Perlmutter has received research funding from National Institutes of Health NS075321, NS103957, NS107281, NS092865, U10NS077384, NS097437, U54NS116025, U19 NS110456, AG050263, AG-64937, NS097799, NS075527, ES029524, NS109487, R61 AT010753, (NCATS, NINDS, NIA), R01NS118146, R01AG065214, Department of Defense (DOD W81XWH-217-1-0393), Michael J FoxFoundation, Barnes-Jewish Hospital Foundation (Elliot Stein Family Fund and Parkinson disease research fund), American Parkinson Disease Association (APDA) Advanced Research Center at Washington University, Missouri Chapter of the APDA, Paula and Rodger Riney Fund, Jo Oertli Fund, Huntington Disease Society of America, Murphy Fund, N. Grant Williams Fund and CHDI. He co-directs the Dystonia Coalition, which received the majority of its support through the NIH (grants NS116025, NS065701 from the National Institutes of Neurological Disorders and Stroke, TR 001456 from the Office of Rare Diseases Research at the National Center for Advancing Translational Sciences). Dr. Perlmutter has provided medical legal consultation to Wood, Cooper and Peterson, LLC and to Simmons and Simmons LLP. He serves as Director of Medical and Scientific Advisory Committee of the Dystonia Medical Research Foundation, Chair of the Scientific Advisory Committee of the Parkinson Study Group, Chair of the Standards Committee of the Huntington Study Group (honoraria for this one), member of the Scientific Advisory Board of the APDA, Chair of the Scientific and Publication Committee for ENROLL-HD (honoraria from this one), and member of the Education Committee of the Huntington Study Group (honoraria from this one). Dr. Perlmutter has received honoraria from CHDI, Huntington Disease Study Group, Parkinson Study Group, Beth Israel Hospital (Harvard group), U Pennsylvania, Stanford U. Boston University. Meghan C. Campbell receives research support from NIH (NS097437, NS075321, NS097799, NS124378, AG063974, AT010753, AT010753-S1), the McDonnell Center for Systems Neuroscience, the Mallinckrodt Institute of Radiology at WUSTL, the Neurimaging Labs Innovation Award and has received honoraria from the Parkinson Foundation.

Figures

Figure Panel 1
Figure Panel 1
a-1c. Subtypes differences across motor, cognitive, and psychiatric measures. Values represent z-scores for each measure (indicator). Higher scores represent worse function for motor and psychiatric measures; lower scores represent worse function for cognitive domains. PIGD = postural instability and gait difficulty. Figure 1a. Three-class solution reproduced in replication sample (N=100). Significant subtype differences (p<.05) for all measures, except bradykinesia (p=.12), tremor (p=.22) and rigidity (p=.29). Figure 1b. Three-class solution replicated in combined sample (N=262). Significant subtype differences (p<.001) for all measures, except tremor (p=.13). Figure 1c. Four-class solution emerged in combined sample (N=262). Significant subtype differences (p<.001) for all measures, except tremor (p=.54).
Figure Panel 2
Figure Panel 2
a-2c. Scatter plots for discriminant analyses of PD subtypes Figure 2a. 3-class PD subtypes in replication sample (N=100). Significant subtype separation with 95% classification accuracy based on discriminant functions 1 and 2, which accounted for 63.0% and 37.0% of the variance, respectively. Figure 2b. 3-class subtypes in combined sample (N=262). Significant subtype separation with 94% classification accuracy based on discriminant functions 1 and 2, which accounted for 64.5% and 35.5% of the variance, respectively. Figure 2c. 4-class subtypes in combined sample (N=262). Significant subtype separation with 93% classification accuracy based on discriminant functions 1, 2, and 3, which accounted for 49.6%, 32.5%, and 17.9% of the variance, respectively.
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