TY - UNPB
T1 - Large-scale plasma proteomics uncovers preclinical molecular signatures of Parkinson's disease and overlap with other neurodegenerative disorders
AU - Global Neurodegeneration Proteomics Consortium (GNPC)
AU - Homann, Jan
AU - Smith, Alexander G
AU - Morgan, Sarah
AU - Frick, Elisabet A
AU - Liu, Fangyu
AU - Viallon, Vivian
AU - Maurya, Rashmi
AU - Korologou-Linden, Roxanna
AU - Dobricic, Valerija
AU - Ohlei, Olena
AU - Deecke, Laura
AU - Hajizadah, Fatema
AU - Zhao, Yujia
AU - Artaud, Fanny
AU - Smith-Byrne, Karl
AU - Kolijn, P Martijn
AU - Huerta, Jose Maria
AU - Winter, Nils
AU - Guevara, Marcela
AU - Jimenez-Zabala, Ana
AU - Sánchez, María José
AU - Trobajo-Sanmartín, Camino
AU - Cabrera-Castro, Natalia
AU - Vinagre, Ana
AU - Petrova, Dafina
AU - Sieri, Sabina
AU - Key, Tim J
AU - Wareham, Nick
AU - Kaaks, Rudolph
AU - Travis, Ruth C
AU - Hahn, Tim
AU - Baker, Susan
AU - Kelly, Sean M
AU - Vermeulen, Roel
AU - Peters, Susan
AU - Masala, Giovanna
AU - Sacerdote, Carlotta
AU - Finkel, Nancy
AU - Elbaz, Alexis
AU - Hess, Moritz
AU - Katzke, Verena
AU - Bertram, Lars
AU - Gudnason, Vilmundur
AU - Robinson, Oliver
AU - Chen, Honglei
AU - Middleton, Lefkos
AU - Winchester, Laura M
AU - Tzoulaki, Ioanna
AU - Gudmundsdottir, Valborg
AU - Walker, Keenan A
PY - 2025/7/30
Y1 - 2025/7/30
N2 - 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.
AB - 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.
U2 - 10.1101/2025.07.30.25332433
DO - 10.1101/2025.07.30.25332433
M3 - Preprint
C2 - 40766128
BT - Large-scale plasma proteomics uncovers preclinical molecular signatures of Parkinson's disease and overlap with other neurodegenerative disorders
PB - medRxiv
ER -