AI Article Synopsis

  • Parkinson's disease (PD) is linked to the loss of dopamine-producing neurons and the formation of Lewy bodies, but there are currently no definitive diagnostic methods for it. This study sought to identify potential biomarkers for the disease, focusing on immune cell involvement.
  • Researchers analyzed multiple datasets to find differentially expressed genes (DEGs), identifying 62 DEGs associated with neurotransmission and dopamine metabolism, and used various computational methods to pinpoint seven key diagnostic genes.
  • The identified genes (SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1) showed high sensitivity and specificity for PD diagnosis, and a higher presence

Article Abstract

Parkinson's disease (PD) is a progressive neurodegenerative disease whose etiology is attributed to development of Lewy bodies and degeneration of dopaminergic neurons in the substantia nigra (SN). Currently, there are no definitive diagnostic indicators for PD. In this study, we aimed to identify potential diagnostic biomarkers for PD and analyzed the impact of immune cell infiltrations on disease pathogenesis. The PD expression profile data for human SN tissue, GSE7621, GSE20141, GSE20159, GSE20163 and GSE20164 were downloaded from the Gene Expression Omnibus (GEO) database for use in the training model. After normalization and merging, we identified differentially expressed genes (DEGs) using the Robust rank aggregation (RRA) analysis. Simultaneously, DEGs after batch correction were identified. Gene interactions were determined through venn Diagram analysis. Functional analyses and protein-protein interaction (PPI) networks were used to the identify hub genes, which were visualized through Cytoscape. A Lasso Cox regression model was employed to identify the potential diagnostic genes. The GSE20292 dataset was used for validation. The proportion of infiltrating immune cells in the samples were determined via the CIBERSORT method. Sixty-two DEGs were screened in this study. They were found to be enriched in nerve conduction, dopamine (DA) metabolism, and DA biosynthesis Gene Ontology (GO) terms. The PPI network and Lasso Cox regression analysis revealed seven potential diagnostic genes, namely SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1, were subsequently validated in peripheral blood samples obtained from healthy control (HC) and PD patients, as well as in the GSE20292 dataset. The results revealed the exceptional sensitivity and specificity of these genes in PD diagnosis and monitoring. Moreover, PD patients exhibited a higher number of plasma cells, compared to HC individuals. The SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1 are potential diagnostic biomarkers for PD. Our findings also reveal the essential roles of immune cell infiltration in both disease onset and trajectory.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10810830PMC
http://dx.doi.org/10.1038/s41598-024-52276-0DOI Listing

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