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June 13, 2026Frontiers in NeurologyOpen Access

Discovery of a preliminary urinary metabolite panel for Parkinson’s disease: a pilot study using paired patient-spouse samples and machine learning consensus

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Authors

QCQian-Qian ChenDGDe-Hai GouJHJin-Yu Huang

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Overview

Pilot study identifies a five-metabolite panel for Parkinson's disease, suggesting potential diagnostic biomarkers.

Key Points

  • This study aims to identify non-invasive urinary biomarkers for Parkinson's disease by leveraging matched-pair samples.
  • Performed untargeted LC-MS metabolomics on urine samples from 15 matched pairs of PD patients and their healthy spouses.
  • Identified differential features using VIP > 1.0 and p < 0.05 with a multi-model consensus approach (RF, SVM, PLS-DA).
  • Filtered 2,640 annotated metabolites for pharmacological relevance and collinearity.
  • Defined a five-metabolite panel including Cyanuric acid and dADP.
  • Achieved promising internal discriminative performance with AUC > 0.95 despite small sample size.
  • Results highlight the effectiveness of controlled design in isolating PD-specific metabolic signatures.

Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/6a2cf2a9faef96ed7f055768https://doi.org/10.3389/fneur.2026.1763253
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