Large-scale plasma proteomics uncovers preclinical molecular signatures of Parkinson's disease and overlap with other neurodegenerative disorders

Parkinson's disease (PD) remains incurable, with a long preclinical phase currently undetectable by existing methods. In the largest proteomic study in neurodegenerative diseases to date, we analyzed blood samples from ~74,000 individuals across discovery and validation cohorts. In the EPIC4PD discovery case-cohort, large-scale profiling of 7,285 proteins (SomaScan-7K) in 4,538 initially unaffected participants (574 incident cases) identified 17 proteins that predict PD up to 28 years before diagnosis. Additional proteins revealed sex-specific effects and time-dependent effect trajectories, capturing disease progression before symptom onset. Replication in three prospective cohorts (n=64,856; 1,034 incident cases) confirmed at least 12 key pre-diagnostic biomarkers with strong evidence, including TPPP2, HPGDS, ALPL, MFAP5, OGFR, ACAD8, TCL1A, GPC4, GSTA3, LCN2, KRAS, and GJA1. Preclinical biomarkers showed 86% concordant effect directions in independent prevalent PD cases (n=2,592; p=1.6×10 -19). Furthermore, in the longitudinal Tracking PD cohort (n=794), HPGDS and MFAP5 also predicted cognitive decline. Notably, several of the identified PD biomarkers overlapped with those for incident Alzheimer's disease and amyotrophic lateral sclerosis, indicating shared molecular signatures. A machine learning-derived protein score improved PD risk prediction in external validation. This extensive proteomics effort identified novel, actionable biomarkers opening new avenues for early PD risk stratification and precision medicine.