Updated Parkinson's disease motor subtypes classification and correlation to CSF HVA and 5-HIAA levels
Jessika Suescun1, Christopher Adams2, Kelly Block3, Emily Tharp1, Timothy Ellmore4, Mya Schiess1
1The University of Texas Health Science Center at Houston, 2The University of Washington, 3Oregon Health & Science University, 4The City College of New York
Objective:

To update a motor subtypes classification using the MDS-UPDRS and determine if CSF neurotransmitter profiles (HVA and 5-HIAA) are different between MDS-UPDRS subtypes in a cohort from the Parkinson's Progression Marker Initiative (PPMI).

Background:

Schiess et al  designed a UPDRS motor classification of Parkinson's Disease (PD) that has been widely used,  but in the last decade, the field has moved towards the use of the MDS-UPDRS.

Design/Methods:

UPDRS and MDS-UPDRS scores were collected for 20 PD patients. Akinetic-rigid (AR), Tremor-dominant (TD), and Mixed (MX) subtypes were calculated using a UPDRS formula, and a new ratio was developed for MDS-UPDRS. This new formula was subsequently applied to 95 PD patients from the PPMI dataset, and subtyping was correlated to neurotransmitter levels. Data were analyzed using receiver operating characteristic models and ANOVA.

Results:

Compared to previous UPDRS classifications, the new MDS-UPDRS AR/TD ratios produced significantly different areas under the curves (AUC). The optimal sensitivity and specificity cutoff scores were >0.82 for TD, <0.71 for AR classifications and Mixed >0.71 and <0.82. Analysis of variance showed significant differences in 5-HIAA levels between the HC and AR group. Logistic models utilizing neurotransmitter levels and MDS-UPDRS motor scores showed significant AUCs for MDS-UPDRS classifications.

Conclusions:

This MDS-UPDRS motor subtype classification system provides a method to transition from the original UPDRS to the newer MDS-UPDRS and offers a reliable and quantifiable tool for monitoring disease progression that is supported by neurotransmitter levels.

10.1212/WNL.0000000000203604