Identification of a robust multitarget protein panel for Parkinson’s disease via absolute quantification and large-scale external replication
Clicks: 3
ID: 321312
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
0.6
/100
3 views
0 readers
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #52 of 113 articles by views in Brain communications
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Abstract This study aimed to identify and validate a robust, generalizable panel of plasma protein biomarkers to improve diagnostic precision in Parkinson’s disease. We analyzed plasma samples from 12 patients with [18F]-FP-CIT PET-confirmed Parkinson’s disease and 15 healthy controls (HC) using the Olink Target 96 Inflammation Panel to identify differentially expressed proteins. Candidate biomarkers were subsequently validated through absolute quantification using Luminex and Olink Flex platforms in an independent cohort of 46 patients with Parkinson’s disease and 33 amyloid-negative and cognitively normal control participants. To assess generalizability, the findings were replicated across multiple heterogeneous populations using large-scale datasets from the UK Biobank and Global Neurodegeneration Proteomics Consortium (GNPC) cohorts. Markers of neurodegeneration (neurofilament light chain [NfL]) and Alzheimer’s disease (phosphorylated tau [pTau181], amyloid β [Aβ]42, Aβ40) co-pathology were measured using the single molecule array (Simoa) platform. Our analyses revealed elevated levels of interleukin (IL)-10 and IL-17C and reduced levels of urokinase plasminogen activator (uPA) and neurotrophin-3 (NTF3) in patients with Parkinson’s disease. These findings were confirmed in the validation cohort. Multitarget models demonstrated superior diagnostic performance over individual markers, with the combination of IL-17C and uPA achieving the highest discrimination (area under the curve [AUC] = 0.780). External validation in the UK Biobank and GNPC datasets confirmed consistent directional changes of three candidates (IL-17C, NTF3, and uPA), reinforcing the biological relevance of these markers. Notably, while NfL levels were significantly elevated in Parkinson’s disease, no significant differences were observed for pTau181 levels or Aβ42/Aβ40 ratios. These findings identify a specific plasma protein panel, particularly the combination of IL-17C and uPA, as a robust and generalizable diagnostic signature that captures fundamental pathophysiological aspects of Parkinson’s disease and enhances diagnostic precision alongside established biomarkers.
| Reference Key |
openalex_W7168754686
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Ho-Won Lee, Youngtae Choi, Shinrye Lee, Junsu Kim, Min‐Tae Jeon, Myungjin Jo, Gyuri Park, Jin‐Sung Park, Do-Geun Kim, Mookyung Cheon, Hyung‐Jun Kim |
| Journal | Brain communications |
| Year | 2026 |
| DOI |
10.1093/braincomms/fcag282
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.