101. Plasma proteomics identify biomarkers predicting Parkinson's disease up to 7 years before symptom onset.
- Author
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Hällqvist J, Bartl M, Dakna M, Schade S, Garagnani P, Bacalini MG, Pirazzini C, Bhatia K, Schreglmann S, Xylaki M, Weber S, Ernst M, Muntean ML, Sixel-Döring F, Franceschi C, Doykov I, Śpiewak J, Vinette H, Trenkwalder C, Heywood WE, Mills K, and Mollenhauer B
- Subjects
- Humans, Male, Female, Aged, Middle Aged, Machine Learning, REM Sleep Behavior Disorder blood, REM Sleep Behavior Disorder diagnosis, Case-Control Studies, Mass Spectrometry, Parkinson Disease blood, Parkinson Disease diagnosis, Biomarkers blood, Proteomics methods
- 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., (© 2024. The Author(s).)
- Published
- 2024
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