Identification of Distinct Blood-based Biomarkers in Early Stage of Parkinson's Disease

Overview

Journal Neurol Sci

Specialty Neurology

Date 2019 Dec 13

PMID 31828678

Citations 13

Authors

Yingyan Wu

Qian Yao

Guo-Xin Jiang

Gang Wang

Qi Cheng

Affiliations

Soon will be listed here.

Abstract

Parkinson's disease (PD) is a slowly progressive geriatric disease, which can be one of the leading causes of serious socioeconomic burden in the aging society. Clinical trials suggest that prompt treatment of early-stage Parkinson's disease (EPD) may slow down the disease progress and have a better response. Therefore, conducting proteomics study to identify biomarkers for the diagnosis and disease-modifying therapies of EPD is vital. We aimed at identifying distinct protein autoantibody biomarkers of EPD by using the database of GSE62283 based on the platform GPL13669 downloaded from Gene Expression Omnibus database. Differentially expressed proteins (DEPs) between the EPD group (n = 103) and the normal control (NC) group (n = 111) were identified by protein-specific t test. Cluster analysis of DEPs was conducted by protein-protein interaction network to detect hub proteins. The hub proteins were then evaluated to determine the distinct biomarkers by principal component analysis, as well as functional and pathway enrichment analysis. Their biological functions were confirmed by gene ontology functional (GO) and Kyoto encyclopedia of genes and genomes pathway enrichment (KEGG). Two biomarkers, mitochondrial ribosome recycling factor (MRRF) and ribosomal protein S18 (RPS18), distinguished the EPD samples from the NC samples, and they were regarded as high-confidence distinct protein autoantibody biomarkers of EPD. The most significant GO function was protein serine/threonine kinase activity (GO: 0004674) and most of DEPs were enriched in ATP binding in molecular function category (GO: 0005524). These results may help in establishing the prompt and accurate diagnosis of EPD and may also contribute to develop mechanism-based treatments.

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