Evidence map›Paper›PMID 40753721›Full record

ArticleEBioMedicine2025

Discovery and validation of biomarkers for Parkinson's disease from human cerebrospinal fluid using mass spectrometry-based proteomics analysis.

Sungtaek Oh, Jaehun Jung, Jinhyeok Kim, Yura Jang, Catherine C Bakker, Alexander Y Pantelyat, Zhen Zhang, Ted M Dawson, Chan Hyun Na, Liana S Rosenthal

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EBioMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Sungtaek OhNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jaehun JungDepartment of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jinhyeok KimNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Yura JangNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Catherine C BakkerDepartment of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Alexander Y PantelyatDepartment of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Zhen ZhangDepartment of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Oncology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: zzhang7@jhmi.edu.
Ted M DawsonNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Solomon H. Snyder Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Physiology, Pharmacology and Therapeutics, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Diana Helis Henry Medical Research Foundation, New Orleans, LA, USA. Electronic address: tdawson@jhmi.edu.
Chan Hyun NaNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; Diana Helis Henry Medical Research Foundation, New Orleans, LA, USA. Electronic address: chanhyun@jhmi.edu.
Liana S RosenthalDepartment of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. Electronic address: Liana.Rosenthal@jhmi.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProteomic biomarkers for Parkinson's disease (PD) are critical for identifying new targets for disease-modifying therapies and expanding our understanding of disease pathophysiology.

methodsDeep proteome analysis of a cerebrospinal fluid (CSF) cohort (40 PD, 40 controls) coupled with previous data from the substantia nigra (SN) proteome was used to discover low abundance biomarkers involved in PD pathogenesis. We validated our findings using parallel reaction monitoring mass spectrometry with an independent cohort of CSF samples (80 PD, 80 controls). We further evaluated our biomarkers with a separate cohort of 80 individuals with Dementia with Lewy Bodies (DLB). We then correlated our candidate biomarkers with motor and cognitive performance.

findingsWe identified 3683 unique proteins, 1425 of them quantified across all 80 discovery samples and 505 that separated PD from controls. Using a stepwise criterion and integrating with 1140 differentially expressed proteins in SN, we identified 34 candidate biomarker proteins. The validation study resulted in 8 proteins (VSTM2A, VGF, SCG2, PI16, OMD, FAM3C, EPHA4, and CCK) with expression patterns and effect sizes like the discovery set. When controlling for age and gender, CCK and OMD maintained their significance and two additional proteins trended toward significance (VGF and PI16, p = 0.057). PI16 and OMD were upregulated in PD, while the others were downregulated. Our investigation is the first to our knowledge to identify PI16 as a possible biomarker and to identify CCK in the CSF of individuals with PD. Combining 4 of the proteins had modest ability to separate PD from controls. CCK and VGF significantly predicted MoCA total scores amongst the DLB group.

interpretationThese candidate biomarkers add to our understanding of PD pathophysiology and the relationship between PD and DLB. They provide further research directions toward disease-modifying therapies.

fundingNational Institute of Neurological Disorders and Stroke.

Indexed as

BiomarkersParkinson DiseaseProteomicsAgedAged, 80 and overFemaleHumansMaleMass SpectrometryMiddle AgedProteomeBiomarkersProteomeBiomarkersCerebrospinal fluidsMass spectrometryParkinson’s diseaseProteomics

Identifiers

PMID40753721
PMCPMC12368294

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.