Objective: To identify pre-diagnostic biomarkers for Parkinson’s Disease (PD) from the plasma proteome.
Background: The plasma proteome is a non-invasive and accessible measure to assess patient health. Diagnosis of PD is primarily made from the clinical presentation of motor symptoms in patients. These symptoms are due to the progressive loss of dopaminergic neurons in the substantia nigra. Investigating the differences in plasma proteomic profiles obtained from individuals prior to a clinical diagnosis of PD compared to controls may benefit the understanding of early pathogenesis and improve detection and diagnosis leading to better therapeutic outcomes.
Method: Plasma proteomic profiles for healthy controls, individuals who develop PD, and individuals already diagnosed with PD are available from the Accelerating Medicines Partnership program for Parkinson’s disease (AMP-PD) and UKBioBank (UKBB). Normalized protein expression (NPX) values from UKBB (n=33,424) are fit in a logistic model to identify significantly associated proteins with PD compared to those without PD. This is followed by targeted analysis using a survival model to assess association of these proteins with time to PD diagnosis. Significant proteins are evaluated for differential expression in AMP-PD (n=149) between the prodromal PD participants and the controls.
Results: We identified 64 proteins associated with PD from our logistic model. Of these, 28 are also significant in the survival analysis. In the prodromal group, GFRA1 (log(Fold Change)=0.176, Adj. P=0.043) and OGN (log(Fold Change)=0.265, Adj. P=0.007) were upregulated compared to controls.
Conclusion: We identified 28 proteins significantly associated with PD both prior to and post clinical diagnosis. Of these proteins, GFRA1 and OGN were replicated in a separate study as differentially expressed in prodromal compared to control subjects. Both GFRA1 and OGN have been previously reported to be neuroprotective and involved in the maintenance and survival of dopamine neurons in the nervous system.
To cite this abstract in AMA style:
M. Ta, E. Appleton, S. Khosousi, A. Sturchio, I. Markaki, W. Paslawski, C. Blauwendraat, M. Nalls, A. Singleton, P. Svenningsson, H. Iwaki. Identification of Pre-Diagnostic Biomarkers for Parkinson’s Disease from Plasma Proteome [abstract]. Mov Disord. 2024; 39 (suppl 1). https://www.mdsabstracts.org/abstract/identification-of-pre-diagnostic-biomarkers-for-parkinsons-disease-from-plasma-proteome/. Accessed November 23, 2024.« Back to 2024 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/identification-of-pre-diagnostic-biomarkers-for-parkinsons-disease-from-plasma-proteome/