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. 2021 Dec 13:15:765765.
doi: 10.3389/fnins.2021.765765. eCollection 2021.

Hoehn and Yahr Stage and Striatal Dat-SPECT Uptake Are Predictors of Parkinson's Disease Motor Progression

Collaborators, Affiliations

Hoehn and Yahr Stage and Striatal Dat-SPECT Uptake Are Predictors of Parkinson's Disease Motor Progression

Holly Jackson et al. Front Neurosci. .

Abstract

Currently, no treatments available for Parkinson's disease (PD) can slow PD progression. At the early stage of the disease, only a subset of individuals with PD progress quickly, while the majority have a slowly progressive form of the disease. In developing treatments that aim to slow PD progression, clinical trials aim to include individuals who are likely to progress faster, such that a treatment effect, if one exists, can be identified easier and earlier. The aim of the present study was to identify baseline predictors of clinical progression in early PD. We analyzed 12-month data acquired from the PASADENA trial Part 1 (NCT03100149, n = 76 participants who were allocated to the placebo arm and did not start symptomatic therapy) and the Parkinson's Progression Markers Initiative (PPMI) study (n = 139 demographically and clinically matched participants). By using ridge regression models including clinical characteristics, imaging, and non-imaging biomarkers, we found that Hoehn and Yahr stage and dopamine transporter single-photon emission computed tomography specific binding ratios (Dat-SPECT SBR) in putamen ipsilateral to the side of motor symptom onset predicted PD progression at the early stage of the disease. Further studies are needed to confirm the validity of these predictors to identify with high accuracy individuals with early PD with a faster progression phenotype.

Keywords: Dat-SPECT imaging; MDS-UPDRS (Movement Disorder Society revision of Unified Parkinson’s Disease Rating Scale); PASADENA; PPMI (Parkinson’s Progression Markers Initiative); Parkinson’s disease; disease stage; progression predictors; ridge regression.

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Conflict of interest statement

HJ was a paid intern of F. Hoffmann-La Roche Ltd. JA-C, KT, and GP were full-time employees and shareholders of F. Hoffmann-La Roche Ltd.

Figures

FIGURE 1
FIGURE 1
Plots showing MDS-UPDRS part III scores of the PD participants on the placebo arm in PASADENA. (A) Distribution of change from baseline. (B) Smoothed average score by week of visit.
FIGURE 2
FIGURE 2
Forest plots showing difference in baseline characteristics between progressors and non-progressors in the placebo arm from PASADENA. (A,B) Standardized mean difference (80% confidence intervals). (C) Odds ratio (80% confidence intervals); for each variable, the reference group is listed. All plots were calculated using 1000 bootstrap samples.
FIGURE 3
FIGURE 3
ROC curves and AUC for each prediction model. (A) Clinically selected prediction model 1. (B) Clinically selected prediction model 2. (C) Data driven prediction model 1. (D) Data driven prediction model 2.

References

    1. Archer K. J., Kimes R. V. (2008). Empirical characterization of random forest variable importance measures. Comput. Stat. Data Anal. 52 2249–2260. 10.1016/j.csda.2007.08.015 - DOI
    1. Belle K., Shabazz F. S., Nuytemans K., Davis D. A., Ali A., Young J. L., et al. (2017). Generation of disease-specific autopsy-confirmed iPSCs lines from postmortem isolated Peripheral Blood Mononuclear Cells. Neurosci. Lett. 637 201–206. 10.1016/j.neulet.2016.10.065 - DOI - PubMed
    1. Benedetti R. (2010). Scoring rules for forecast verification. Mon. Weather Rev. 138 203–211. 10.1175/2009mwr2945.1 - DOI
    1. Canty A., Boot R. B. (2020). Bootstrap R (S-Plus) Functions. 2020. R package version. 1.3-25.
    1. Chernick M. R., LaBudde R. A. (2014). An Introduction to Bootstrap Methods with Applications to R. Hoboken: John Wiley & Sons.