ArticleNPJ Parkinson's disease2021
Identification of cerebrospinal fluid biomarkers for parkinsonism using a proteomics approach.
Article in NPJ Parkinson's disease, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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Who cites it
13 citing papers in PubMed, 20 citations in OpenAlex.
- Multi-omics approaches to parkinsonism: genomic, proteomic, and non-coding RNA perspectives.Molecular biology reports · 2026Review
- Article
- Integrative Metabolome and Proteome Analysis of Cerebrospinal Fluid in Parkinson's Disease.International journal of molecular sciences · 2024Review
- Hypoxic-Ischemic Insult Alters Polyamine and Neurotransmitter Abundance in the Specific Neonatal Rat Brain Subregions.ACS chemical neuroscience · 2024Article
- The potential of phosphorylated α-synuclein as a biomarker for the diagnosis and monitoring of multiple system atrophy.CNS neuroscience & therapeutics · 2024Review
- Proteomic profiling of cerebrospinal fluid in pediatric myelin oligodendrocyte glycoprotein antibody-associated disease.World journal of pediatrics : WJP · 2024Article
- High-Throughput CSF Proteomics and Machine Learning to Identify Proteomic Signatures for Parkinson Disease Development and Progression.Neurology · 2023Observational
- Plasma Metabolic Analysis Reveals the Dysregulation of Short-Chain Fatty Acid Metabolism in Parkinson's Disease.Molecular neurobiology · 2023Article
- A proteogenomic view of Parkinson's disease causality and heterogeneity.NPJ Parkinson's disease · 2023Article
- Temporal proteomics of human cerebrospinal fluid after severe traumatic brain injury.Journal of neuroinflammation · 2022Observational
- Opportunities and challenges of alpha-synuclein as a potential biomarker for Parkinson's disease and other synucleinopathies.NPJ Parkinson's disease · 2022Review
- Cerebrospinal Fluid Metabolome in Parkinson's Disease and Multiple System Atrophy.International journal of molecular sciences · 2022Review
- A Species-Specific Strategy for the Identification of HemocoagulaseFrontiers in molecular biosciences · 2022Article
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
The aim of our study was to investigate cerebrospinal fluid (CSF) tryptic peptide profiles as potential diagnostic biomarkers for the discrimination of parkinsonian disorders. CSF samples were collected from individuals with parkinsonism, who had an uncertain diagnosis at the time of inclusion and who were followed for up to 12 years in a longitudinal study. We performed shotgun proteomics to identify tryptic peptides in CSF of Parkinson's disease (PD, n = 10), multiple system atrophy patients (MSA, n = 5) and non-neurological controls (n = 10). We validated tryptic peptides with differential levels between PD and MSA using a newly developed selected reaction monitoring (SRM) assay in CSF of PD (n = 46), atypical parkinsonism patients (AP; MSA, n = 17; Progressive supranuclear palsy; n = 8) and non-neurological controls (n = 39). We identified 191 tryptic peptides that differed significantly between PD and MSA, of which 34 met our criteria for SRM development. For 14/34 peptides we confirmed differences between PD and AP. These tryptic peptides discriminated PD from AP with moderate-to-high accuracy. Random forest modelling including tryptic peptides plus either clinical assessments or other CSF parameters (neurofilament light chain, phosphorylated tau protein) and age improved the discrimination of PD vs. AP. Our results show that the discovery of tryptic peptides by untargeted and subsequent validation by targeted proteomics is a suitable strategy to identify potential CSF biomarkers for PD versus AP. Furthermore, the tryptic peptides, and corresponding proteins, that we identified as differential biomarkers may increase our current knowledge about the disease-specific pathophysiological mechanisms of parkinsonism.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.