Machine learning analysis of population-wide plasma proteins identifies hormonal biomarkers of Parkinson's disease - PubMed
3 hours ago
- #Biomarkers
- #Parkinson's disease
- #Machine learning
- The study uses machine learning on plasma proteomics from 43,408 UK Biobank subjects to identify Parkinson's disease biomarkers.
- Identified biomarkers include known markers DDC and CALB2, and new markers linked to JAK-STAT, PI3K-AKT pathways, and hormonal signaling.
- Biomarkers correlate with disease severity (UPDRS scores) and are classified as protective or risk-associated, aiding in patient stratification and therapy development.