Targeted discovery and validation of plasma biomarkers of Parkinson's disease

Abstract

Despite extensive research, an unmet need remains for protein biomarkers of Parkinson's disease (PD) in peripheral body fluids, especially blood, which is easily accessible clinically. The discovery of such biomarkers is challenging, however, due to the enormous complexity and huge dynamic range of human blood proteins, which are derived from nearly all organ systems, with those originating specifically from the central nervous system (CNS) being exceptionally low in abundance. In this investigation of a relatively large cohort (∼300 subjects), selected reaction monitoring (SRM) assays (a targeted approach) were used to probe plasma peptides derived from glycoproteins previously found to be altered in the CNS based on PD diagnosis or severity. Next, the detected peptides were interrogated for their diagnostic sensitivity and specificity as well as the correlation with PD severity, as determined by the Unified Parkinson's Disease Rating Scale (UPDRS). The results revealed that 12 of the 50 candidate glycopeptides were reliably and consistently identified in plasma samples, with three of them displaying significant differences among diagnostic groups. A combination of four peptides (derived from PRNP, HSPG2, MEGF8, and NCAM1) provided an overall area under curve (AUC) of 0.753 (sensitivity: 90.4%; specificity: 50.0%). Additionally, combining two peptides (derived from MEGF8 and ICAM1) yielded significant correlation with PD severity, that is, UPDRS (r = 0.293, p = 0.004). The significance of these results is at least two-fold: (1) it is possible to use a targeted approach to identify otherwise very difficult to detect CNS related biomarkers in peripheral blood and (2) the novel biomarkers, if validated in independent cohorts, can be employed to assist with clinical diagnosis of PD as well as monitoring disease progression.

Keywords: Parkinson’s disease; peripheral biomarkers; selected reaction monitoring; targeted mass spectrometry.

Figure 1

Brief workflow outlining the pipeline for screening plasma PD glycoprotein biomarkers by SRM. In the Pilot study, a primary synthetic peptide library containing 133 unpurified, deamidated N-glycopeptides was used to generate SRM assays and test the detectability of these formerly N-glycosylated peptides in glycocaptured plasma. Refined SRM assays with optimized settings including retention time (RT) were applied in next stages in the pipeline. In initial validation, 50 N-glycopeptides that could be detected in the Pilot study were measured in a cohort including 15 PD, AD, and control samples pooled from 75 PD, 15 AD, and 30 control individuals, respectively. The final SRM assay library containing 12 purified, deamidated N-glycopeptides was then used to detect the candidate biomarkers in an independent validation cohort for ROC calculation and assessment of disease severity association (n = 162).

Figure 2

Heat map of hierarchical clustering analysis of the 50 N-glycopeptides that were detected in the initial validation cohort containing 15 pooled control, AD, and PD plasma samples. The analysis was based on SRM measured peptide relative abundance against average of three pooled controls and conducted using average linkage and Euclidean distance. PD1, PD2, and PD3 represent PD at early, middle, and late stages of the disease, respectively, based on UPDRS. (Also see Table 1.)

Figure 3

Logistic regression of a panel of four N-glycopeptides and correlation with PD progression. (A) Receiver operating characteristic (ROC) curve and corresponding area under the curve (AUC) of the classifier in distinguishing PD from controls are presented. This classifier includes four formerly N-linked glycopeptides (PRNP, HSPG2, MEGF8, and NCAM1). AUC = 0.753, sensitivity = 90.4%, specificity = 50.0%. (B) Combination of two N-glycopeptides (ICAM 1 and MEGF8) correlates with PD progression. Pearson correlation: r = 0.293, p = 0.004. UPDRS_predict = 23–14 * ICAM1 + 11 * MEGF8.