Hidden Messages in Vesicles: Unveiling miRNA Biomarkers for Parkinson’s Disease through Next-Generation Sequencing

Abstract

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the gradual loss of dopaminergic neurons in the substantia nigra. PD usually leads to hallmark motor symptoms such as bradykinesia and resting tremor. Although current therapies can alleviate symptoms, the disease remains incurable. MiRNAs derived from extracellular vesicles (EV-derived) have shown great potential as biomarkers for various diseases, including PD. Therefore, finding miRNA biomarkers could enable early disease detection and support personalised treatment strategies. We aimed yo profile EV-derived miRNAs in Parkinson’s disease patients and healthy controls using next-generation sequencing (NGS) to identify potential biomarkers for the disease. EV-derived miRNAs were isolated from the blood serum of five PD patients and five healthy controls. The samples were then subjected to NGS. Sequencing data were analysed using principal component analysis (PCA), DESeq2 for differential expression and KEGG pathway analysis. PCA revealed two distinct clusters corresponding to healthy controls and PD patients. Differential expression analysis using DESeq2 identified ten miRNAs significantly deregulated in PD patients compared to controls. KEGG pathway analysis showed that these miRNAs are involved in pathways, like PD, Alzheimer’s disease, dopaminergic synapse, MAPK signaling, suggesting potential links to molecular mechanisms underlying PD. We identified ten miRNAs as potential biomarkers for Parkinson’s disease. These miRNAs were found to be involved in neurodegeneration-related pathways, suggesting their possible role in PD pathogenesis. Further studies with larger sample sizes are required to validate these findings and better characterize the expression patterns of these miRNAs.