Plasma proteomics identify biomarkers predicting Parkinson's disease up to 7 years before symptom onset

Nat Commun. 2024 Jun 18;15(1):4759. doi: 10.1038/s41467-024-48961-3.

Abstract

Parkinson's disease is increasingly prevalent. It progresses from the pre-motor stage (characterised by non-motor symptoms like REM sleep behaviour disorder), to the disabling motor stage. We need objective biomarkers for early/pre-motor disease stages to be able to intervene and slow the underlying neurodegenerative process. Here, we validate a targeted multiplexed mass spectrometry assay for blood samples from recently diagnosed motor Parkinson's patients (n = 99), pre-motor individuals with isolated REM sleep behaviour disorder (two cohorts: n = 18 and n = 54 longitudinally), and healthy controls (n = 36). Our machine-learning model accurately identifies all Parkinson patients and classifies 79% of the pre-motor individuals up to 7 years before motor onset by analysing the expression of eight proteins-Granulin precursor, Mannan-binding-lectin-serine-peptidase-2, Endoplasmatic-reticulum-chaperone-BiP, Prostaglaindin-H2-D-isomaerase, Interceullular-adhesion-molecule-1, Complement C3, Dickkopf-WNT-signalling pathway-inhibitor-3, and Plasma-protease-C1-inhibitor. Many of these biomarkers correlate with symptom severity. This specific blood panel indicates molecular events in early stages and could help identify at-risk participants for clinical trials aimed at slowing/preventing motor Parkinson's disease.

MeSH terms

  • Aged
  • Biomarkers* / blood
  • Case-Control Studies
  • Female
  • Humans
  • Machine Learning
  • Male
  • Mass Spectrometry
  • Middle Aged
  • Parkinson Disease* / blood
  • Parkinson Disease* / diagnosis
  • Proteomics* / methods
  • REM Sleep Behavior Disorder / blood
  • REM Sleep Behavior Disorder / diagnosis

Substances

  • Biomarkers