Identification of a possible proteomic biomarker in Parkinson’s disease: discovery and replication in blood, brain and CSF

Winchester, L. et al. (2023) Identification of a possible proteomic biomarker in Parkinson’s disease: discovery and replication in blood, brain and CSF. Brain Communications, 5(1), fcac343. (doi: 10.1093/braincomms/fcac343) (PMID:36694577) (PMCID:PMC9856276)

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Abstract

Biomarkers to aid diagnosis and delineate the progression of Parkinson’s disease are vital for targeting treatment in the early phases of the disease. Here, we aim to discover a multi-protein panel representative of Parkinson’s and make mechanistic inferences from protein expression profiles within the broader objective of finding novel biomarkers. We used aptamer-based technology (SomaLogic®) to measure proteins in 1599 serum samples, 85 cerebrospinal fluid samples and 37 brain tissue samples collected from two observational longitudinal cohorts (the Oxford Parkinson’s Disease Centre and Tracking Parkinson’s) and the Parkinson’s Disease Brain Bank, respectively. Random forest machine learning was performed to discover new proteins related to disease status and generate multi-protein expression signatures with potential novel biomarkers. Differential regulation analysis and pathway analysis were performed to identify functional and mechanistic disease associations. The most consistent diagnostic classifier signature was tested across modalities [cerebrospinal fluid (area under curve) = 0.74, P = 0.0009; brain area under curve = 0.75, P = 0.006; serum area under curve = 0.66, P = 0.0002]. Focusing on serum samples and using only those with severe disease compared with controls increased the area under curve to 0.72 (P = 1.0 × 10−4). In the validation data set, we showed that the same classifiers were significantly related to disease status (P < 0.001). Differential expression analysis and weighted gene correlation network analysis highlighted key proteins and pathways with known relationships to Parkinson’s. Proteins from the complement and coagulation cascades suggest a disease relationship to immune response. The combined analytical approaches in a relatively large number of samples, across tissue types, with replication and validation, provide mechanistic insights into the disease as well as nominate a protein signature classifier that deserves further biomarker evaluation.

Item Type:Articles
Additional Information:This work was supported by the Monument Trust Discovery Awards (J-0901 and J-1403) Awards and Tracking Parkinson’s (J-1101 and J-1301) from Parkinson’s UK. Additional funds were provided by Dementias Platform UK funded by UK Research and Innovation Medical Research Council [MR/L023784/1 and MR/L023784/2] and by funds awarded by Rosetrees Trust (M937) and John Black Charitable Foundation (ID A2926).
Keywords:Parkinson’s disease, proteomics, biomarker.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Grosset, Professor Donald
Authors: Winchester, L., Barber, I., Lawton, M., Ash, J., Liu, B., Evetts, S., Hopkins-Jones, L., Lewis, S., Bresner, C., Belen Malpartida, A., Williams, N., Gentlemen, S., Wade-Martins, R., Ryan, B., Holgado-Nevado, A., Hu, M., Ben-Shlomo, Y., Grosset, D., and Lovestone, S.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
Journal Name:Brain Communications
Publisher:Oxford University Press
ISSN:2632-1297
ISSN (Online):2632-1297
Published Online:28 December 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Brain Communications 5(1) :fcac343
Publisher Policy:Reproduced under a Creative Commons License

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