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

Medicine and Health

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

J. Hällqvist, M. Bartl, et al.

Discover how a groundbreaking blood test can identify individuals at risk for Parkinson's disease years before symptoms appear! This innovative research by Jenny Hällqvist and colleagues highlights the potential of a targeted mass spectrometry assay in predicting disease onset, offering hope for earlier interventions and clinical trials.... show more
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, Intercellular-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.
Publisher
Nature Communications
Published On
Jun 18, 2024
Authors
Jenny Hällqvist, Michael Bartl, Mohammed Dakna, Sebastian Schade, Paolo Garagnani, Maria-Giulia Bacalini, Chiara Pirazzini, Kailash Bhatia, Sebastian Schreglmann, Mary Xylaki, Sandrina Weber, Marielle Ernst, Maria-Lucia Muntean, Friederike Sixel-Döring, Claudio Franceschi, Ivan Doykov, Justyna Śpiewak, Héloïse Vinette, Claudia Trenkwalder, Wendy E. Heywood, Kevin Mills, Brit Mollenhauer
Tags
Parkinson's disease
blood biomarkers
mass spectrometry
machine learning
early detection
clinical trials
REM sleep behavior disorder
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