Erythrocyte EV Biomarkers for Parkinson's Disease

Example 3

We have identified biomarkers correlating to different states of PD based on the quantification of EV shed from erythrocytes and UPDRS scores. In particular, we have shown a strong correlation between the number of EEV and the clinical expression/stages of PD. Finding this level of correlation in a 60-patient sample size in such a heterogeneous disorder highlights the robustness of the biomarkers identified herein.

Although staging of PD is often done using the H & Y clinical scale, we sought to use the UPDRS given its greater sensitivity and the recent publications validating this approach (Martinez-Martin et al., 2015). Using these scores, we found that mild PD patients—with a UPDRS score lower than 37—are characterized by an increased number of EV during the mild disease stage (correlations=0.886); and that the same pattern repeated itself with patients who had UPDRS scores between 37 and 75 (correlations=0.873). When comparing individual patients from both correlation curves, the dose of levodopa taken daily did not seem to account for the differences, as there was no correlation between the levodopa dose and the number of EEV.

Finally, we herein report an improved method to perform proteomic analysis of EEV in blood samples by removing hemoglobin, a large protein that can easily mask other ones within a protein signature. Indeed, the high dynamic range of protein concentrations in erythrocytes and therefore in EEV, due to the high abundance of hemoglobin, decreases the capacity of the mass spectrometer to detect signals corresponding to low abundance proteins. Analyzing the hemoglobin separately from the other proteins of other molecular weights allowed us to go deeper in the EEV proteome by identifying 129% more proteins than in the initial analysis.

The present description refers to a number of documents, the contents of which are herein incorporated by reference in their entirety.