Transcriptomic analysis of plasma small extracellular vesicles identifies potential diagnostic biomarkers for...

Blood-based biomarkers that can aid diagnosis of Parkinson's Disease (PD) dementia (PDD), and predict PDD onset in people with PD are urgently needed. Plasma small extracellular vesicles (SEV) reflect molecular changes in living human brain. Next-generation RNA-sequencing (RNA-Seq) of PDD plasma SEV can advance our understanding of PDD molecular pathology, and identify blood-based biomarkers. Hence, we conducted the first comprehensive transcriptomic analysis of PDD plasma SEV.

We investigated plasma SEV RNA of PDD, PD, and people without PD or dementia (Controls) using RNA-Seq (n = 15/group; N = 45). SEV were separated by ultracentrifugation, and characterized by cryo-transmission electron microscopy. We identified differentially expressed genes (DEGs) in PDD plasma SEV using an edgeR-based data analysis pipeline and verified them by high-throughput qPCR. We assessed functional implications of identified DEGs using Ingenuity Pathway and causal network analyses.

We identified 51 transcriptome-wide significant (edgeR q < 0.05) DEGs, compared to controls, and 26 transcriptome-wide significant DEGs, compared to PD, in PDD plasma SEV. The identified DEGs, which included WNT5A, MAPT, FOSB, MIR324, MIR574, MIR3161, and MIR6821 were significantly enriched among Tetrahydrofolate salvage, Reelin signalling, tRNA splicing, Wnt signalling, and ERBB signalling pathways. We identified eight potential multiplex plasma SEV RNA biomarker assays that can distinguish PDD from PD with at least 80 % sensitivity and specificity using an artificial intelligence-based algorithm.

Future research on the identified dysfunctional molecular pathways may facilitate discovery of novel therapeutic targets for PDD. Diagnostic biomarker potential of the derived multiplex RNA biomarker assays should be investigated by larger clinical studies.