ArticleNature communications2024
Plasma proteomics identify biomarkers predicting Parkinson's disease up to 7 years before symptom onset.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers, 2 of them syntheses that pooled it.
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Who cites it
69 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Omics research in Parkinson's disease: evolution, integrated analysis, pathogenic mechanisms, biomarkers, and therapeutic targets.Frontiers in molecular neuroscience · 2026Pooled it
- Beyond bacteria: a multi-omics view of the gut-brain axis in Parkinson's disease.Frontiers in cellular and infection microbiology · 2026Pooled it
- Profiling peripheral immune cells in Parkinson's disease: A scoping review.Journal of Parkinson's disease · 2026Review
- Electronic profiling of neuronal extracellular vesicles enables early prediction of Parkinson's disease.Science advances · 2026Article
- Development and validation of a serum peptidomic signature for early detection of asymptomatic ovarian cancer: A multi-center prospective study.Cell reports. Medicine · 2026Article
- Special Issue "Molecular Advances in Biomarkers of Central Nervous System Diseases and Disorders".International journal of molecular sciences · 2026Article
- Pain in Parkinson's disease: bridging pathophysiology, clinical features, and personalized management.The journal of headache and pain · 2026Review
- Sex-aware causal inference assessment of the immune system in complex neurodegenerative diseases.Brain : a journal of neurology · 2026Article
- Translating genomic data into healthcare practice with the Singapore National Precision Medicine program.Nature genetics · 2026Review
- Complement dysregulation during the early phases of synucleinopathy.Acta neuropathologica · 2026Article
- Predicting health and disease: a conceptual framework for AI in preventive and precision medicine.BMJ health & care informatics · 2026Review
- The complement C3-microglial axis in depression of Parkinson's disease: from mechanism to therapeutic intervention.EBioMedicine · 2026Article
- Multi-omics approaches to parkinsonism: genomic, proteomic, and non-coding RNA perspectives.Molecular biology reports · 2026Review
- Leveraging nanoparticle protein corona to advance plasma proteome profiling.Nature communications · 2026Review
- The Ecology of Care in Parkinson's Disease.Movement disorders clinical practice · 2026Article
- Proteomic clocks combined with deep learning phenotypes track eye aging and diseases.NPJ digital medicine · 2026Article
- Systematic Evaluation of Depletion and Enrichment Technologies for Platelet-Free Plasma Proteomics.Journal of proteome research · 2026Article
- A multimodal biomarker strategy to enhance diagnostic precision in neurodegenerative parkinsonism.Nature medicine · 2026Article
- Plasma proteomics for Parkinson's disease classification: cross-cohort benchmarking of proteomic, transcriptomic, and multimodal models.NPJ Parkinson's disease · 2026Article
- Identification of biomarkers for non-invasive diagnosis and risk stratification in prostate cancer using NMR-based metabolomics and machine learning.NPJ precision oncology · 2026Article
9 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
22 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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