Identification of a prospective early motor progression cluster of Parkinson's disease: Data from the PPMI study

J Neurol Sci. 2018 Apr 15;387:103-108. doi: 10.1016/j.jns.2018.01.025. Epub 2018 Jan 31.

Abstract

Aim: The aim of our study is to phenotype PD motor progression, and to detect whether serum, cerebrospinal fluid (CSF), neuroimaging biomarkers and neuropsychological measures characterize PD motor progression phenotypes.

Methods: We defined motor progression as a difference of at least one point in the Hoehn & Yahr (H&Y) scale between the baseline (Visit 0, V0), 12 months (Visit 04, V04) and 36 months (Visit 08, V08) milestones of the Progression Markers Initiative (PPMI) study. H&Y progression events were recorded at each milestone in order to be used as cluster analysis variables, in order to produce progression phenotypes. Subsequently, cross-cluster comparisons prior to and following (pairwise) propensity score matching were performed in order to assess phenotype - defining characteristics.

Results: Four progression clusters where identified: SPPD: Secondarily Progressive PD, H&Y progression between V04 and V08; EPPD: Early Progressive PD. H&Y progression between V0 and V04; NPPD: Non Progressive PD, no H&Y progression; MIPD: Minimally Improving PD, i.e. Minimal H&Y improvement H&Y progression between V04 and V08;. Independent Samples Mann Whitney U tests determined CSF aSyn (p = 0.006, adj p-value = 0.036. I) and Semantic Animal fluency T-score (SFT, p = 0.003, adjusted p-value = 0.016.) as statistically significant cross-cluster characteristics. Following Propensity Score Matching, SFT, Hopkins Verbal Learning Test (Retention/Recall), Serum IGF1, CSF aSyn, DaT-SPECT binding ratios (SBRs) and the Benton Judgement of Line Orientation Test (BJLOT) were determined as statistically significant predictors of cluster differentiation (p < 0.05).

Discussion: SFT, Serum IGF1, CSF aSyn and DaT-SPECT-derived, basal ganglia Striatal Binding Ratios warrant further investigation as possible motor progression biomarkers.

Keywords: Biomarkers; Cluster analysis; Parkinson's disease; Phenotypes; Progression.

MeSH terms

  • Aged
  • Biomarkers / blood*
  • Biomarkers / cerebrospinal fluid*
  • Cluster Analysis
  • Databases, Bibliographic / statistics & numerical data*
  • Disease Progression
  • Female
  • Humans
  • Logistic Models
  • Magnetic Resonance Imaging
  • Male
  • Middle Aged
  • Parkinson Disease / blood*
  • Parkinson Disease / cerebrospinal fluid*
  • Parkinson Disease / diagnostic imaging
  • Parkinson Disease / physiopathology*
  • Phenotype
  • Statistics, Nonparametric

Substances

  • Biomarkers