Plasma acellular transcriptome contains Parkinson's disease signatures that can inform clinical diagnosis

Abstract

We aimed to identify plasma cell-free transcripts (cfRNA) associated with Parkinson's disease (PD) that also have a high predictive value to differentiate PD from healthy controls. Leveraging two independent populations from two different movement disorder centers we identified 2,188 differentially expressed cfRNAs after meta-analysis. The identified transcripts were enriched in PD relevant pathways, such as PD (p=9.26×10^-4), ubiquitin-mediated proteolysis (p=7.41×10^-5) and endocytosis (p=4.21×10^-6). Utilizing in-house and publicly available brain, whole blood, and acellular plasma transcriptomic and proteomic PD datasets, we found significant overlap across dysregulated biological species in the different tissues and the different biological layers. We developed three predictive models containing increasing number of transcripts that can distinguish PD from healthy control with an area under the ROC Curve (AUC) ≥0.85. Finally, we showed that several of the predictive transcripts significantly correlate with symptom severity measured by UPDRS-III. Overall, we have demonstrated that cfRNA contains pathological signatures and has the potential to be utilized as biomarker to aid in PD diagnostics and monitoring.

Figure 1.. Study Design Infographic

depicting the study participants from two independent cohorts, summary of the experimental approach including data processing and analyses, biological contextualization of the results via multiomic data integration with available independent datasets, and leverage of results to build predictive models.

Figure 2.. Multiomic integration summary.

Integration between differential expression analysis of cfRNA (maroon) with A. whole blood RNAseq (orange) and plasma proteomics (light yellow); B. brain RNAseq (dark blue) and CSF proteomics (light blue); C. single nuclei datasets; and D. GWAS data (rosy-brown). The y-axes in panels A, B and D represent −log₁₀ of differential expression p-value, while x-axes represent genomic coordinates of the respective transcript/gene. Dotted lines symbolize the same transcript/gene or its protein product that are significantly differentially expressed across the multiple omic layers displayed in each respective panel, A, B or D.

Figure 3.. Plasma cfRNA capture signatures associated with PD pathology.

A. Scatter plot summarizing the significant results of KEGG pathway analysis, in gold are pathways first captured in all the predictive models and in blue pathways captured in 87 and 191 transcript models; Whisker plot showing the performance of the evaluated predictive models to differentiate between B. PD and HC; C. AD, DLB, or FTD, and HC; and D. AD, DLB, or FTD, and PD.