| Title: | Large-scale proteomic analyses of incident Parkinson's disease reveal new pathophysiological insights and potential biomarkers |
| Journal: | Nature Aging |
| Published: | 20 Feb 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39979637/ |
| DOI: | https://doi.org/10.1038/s43587-025-00818-0 |
Publication 15316
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
The early pathophysiology of Parkinson's disease (PD) is poorly understood. We analyzed 2,920 Olink-measured plasma proteins in 51,804 UK Biobank participants, identifying 859 incident PD cases after 14.45 years. We found 38 PD-related proteins, with six of the top ten validated in the Parkinson's Progression Markers Initiative (PPMI) cohort. ITGAV, HNMT and ITGAM showed consistent significant association (hazard ratio: 0.11-0.57, P = 6.90 × 10−24 to 2.10 × 10−11). Lipid metabolism dysfunction was evident 15 years before PD onset, and levels of BAG3, HPGDS, ITGAV and PEPD continuously decreased before diagnosis. These proteins were linked to prodromal symptoms and brain measures. Mendelian randomization suggested ITGAM and EGFR as potential causes of PD. A predictive model using machine learning combined the top 16 proteins and demographics, achieving high accuracy for 5-year (area under the curve (AUC) = 0.887) and over-5-year PD prediction (AUC = 0.816), outperforming demographic-only models. It was externally validated in PPMI (AUC = 0.802). Our findings reveal early peripheral pathophysiological changes in PD crucial for developing early biomarkers and precision therapies.</p>
13 Authors
- Yi-Han Gan
- Ling-Zhi Ma
- Yi Zhang
- Jia You
- Yu Guo
- Yu He
- Lin-Bo Wang
- Xiao-Yu He
- Yu-Zhu Li
- Qiang Dong
- Jian-Feng Feng
- Wei Cheng
- Jin-Tai Yu
1 Application
| Application ID | Title |
|---|---|
| 19542 | Identifying multi-level biomarkers and disease mechanisms for major mental disorders |
Enabling scientific discoveries that improve human health