Differential gene expression and immune profiling in Parkinson's disease: unveiling potential candidate biomarkers.

Background: Parkinson's disease (PD) represents a common neurodegenerative disorder characterized by a multifaceted interaction with immune infiltration. Despite a well-defined clinical diagnosis, the misdiagnosis rate of PD remains around 20%. The aim of this study is to discover new diagnostic biomarkers for PD and investigate their pathogenesis to improve early intervention and effective management of patients with PD.

Methods: Five PD-related GEO datasets were used: four for training (GSE7621, GSE8397, GSE20186, and GSE20292) and one for validation (GSE26927). Gene expression analysis included batch correction and "RobustRankAggreg" (RRA) methods. Differentially expressed genes (DEGs) were linked to functions via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Hub genes were identified using CytoHubba in Cytoscape and validated with ROC analysis. Real-time quantitative polymerase chain reaction (RT-qPCR) confirmed hub gene expression in PD patients' substantia nigra. CIBERSORT, along with the Wilcoxon test and Least Absolute Shrinkage and Selection Operator (LASSO) regression, analyzed differences in immune cell abundance between PD patients and healthy controls (HC). Spearman's rank correlation in R explored the link between biomarkers and immune cells.

Results: The intersection of two methods identified 124 DEGs in PD. GO analysis revealed enrichment in neurotransmitter transport, while KEGG analysis identified involvement in the dopaminergic synapse pathway. Three hub genes (DDC, NEFL, and SLC18A2) were identified using the "UpSet" R package, and their expression was significantly lower in PD patients than in the HC group (all p < 0.05), as confirmed by RT-qPCR. LASSO regression and ROC analysis demonstrated that SLC18A2 could diagnose PD with high specificity and sensitivity in both training (0.85 and 0.84) and validation sets (1.00 and 0.75). CIBERSORT analysis showed increased memory B cells, activated mast cells, NK cells, and CD8⁺ T cells in PD, with notable differences in the abundance of memory B cells and activated mast cells between PD and HC.

Conclusion: The study identifies SLC18A2 as a potential candidate biomarker for PD and emphasizes the involvement of memory B cells and activated mast cells in the onset and progression of the disease.