Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define putative diagnostic biosignatures for Parkinson’s disease

Author:

Hadisurya MarcoORCID,Li Li,Kuwaranancharoen KananartORCID,Wu XiaofengORCID,Lee Zheng-Chi,Alcalay Roy N.,Padmanabhan Shalini,Tao W. Andy,Iliuk AntonORCID

Abstract

Abstract Background Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene have been recognized as genetic risk factors for Parkinson’s disease (PD). However, compared to cancer, fewer genetic mutations contribute to the cause of PD, propelling the search for protein biomarkers for early detection of the disease. Methods Utilizing 138 urine samples from four groups, healthy individuals (control), healthy individuals with G2019S mutation in the LRRK2 gene (non-manifesting carrier/NMC), PD individuals without G2019S mutation (idiopathic PD/iPD), and PD individuals with G2019S mutation (LRRK2 PD), we applied a proteomics strategy to determine potential diagnostic biomarkers for PD from urinary extracellular vesicles (EVs). Results After efficient isolation of urinary EVs through chemical affinity followed by mass spectrometric analyses of EV peptides and enriched phosphopeptides, we identify and quantify 4476 unique proteins and 2680 unique phosphoproteins. We detect multiple proteins and phosphoproteins elevated in PD EVs that are known to be involved in important PD pathways, in particular the autophagy pathway, as well as neuronal cell death, neuroinflammation, and formation of amyloid fibrils. We establish a panel of proteins and phosphoproteins as novel candidates for disease biomarkers and substantiate the biomarkers using machine learning, ROC, clinical correlation, and in-depth network analysis. Several putative disease biomarkers are further partially validated in patients with PD using parallel reaction monitoring (PRM) and immunoassay for targeted quantitation. Conclusions These findings demonstrate a general strategy of utilizing biofluid EV proteome/phosphoproteome as an outstanding and non-invasive source for a wide range of disease exploration.

Funder

U.S. Department of Health & Human Services | NIH | Center for Information Technology

The Michael J Fox Foundation for Parkinson’s Research Grant# 17453

Publisher

Springer Science and Business Media LLC

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