Towards a blood-based diagnostic panel for confirmation of Parkinson’s Disease (U01)

Alice Chen-Plotkin
PI:
Alice Chen-Plotkin
University of Pennsylvania (Philadelphia, Pennsylvania)

Summary

Dr. Chen-Plotkin has used an proteomics approach (SomaSCAN aptamer platform) to screen >1000 proteins from the plasma of Parkinson’s Disease (PD), Alzheimer’s Disease (AD) and control subjects, discovering, in the process, an eight-protein panel that has potential to confirm PD diagnosis from a blood sample. Specifically, a classifier using these eight proteins could distinguish PD from normal controls with >95% accuracy in a training dataset; even more impressive, accuracy stayed >90% when these same eight protein biomarkers were applied to an independent test set of PD vs. control samples, and to the task of distinguishing PD from AD samples as well.  This application proposes to test the robustness of this preliminary result obtained in 166 samples from the University of Pennsylvania (UPenn), through replication in two major PD cohorts, the Parkinson’s Disease Biomarker Program (PDBP) cohort and, if successful in PDBP, the Parkinson’s Progression Marker Initiative (PPMI) cohort. The potential impact of a blood-based test for confirmation of PD diagnosis is high. At present, PD diagnosis relies almost completely on clinical examination, with accuracy estimated at 70-90%. Diagnostic certainty is particularly difficult in early PD, where, paradoxically, the potential for effective disease-modifying measures may be highest.

Abstract

At present, Parkinson's disease (PD) affects more than 4 million people worldwide, with numbers expected to nearly double by 2030. PD is a progressive neurodegenerative disease, and there are no disease-modifying therapies. Currently, the diagnosis of PD relies almost entirely on clinical examination, with no laboratory-based confirmatory testing available. While clinical accuracy is reasonably high in longitudinally followed patients with moderate symptoms, it is much lower in earlier stages of PD. As a consequence, both for clinical care and to accelerate the development of much-needed therapeutics, a confirmatory diagnostic biomarker would be of great utility. To meet this need, we previously used a novel aptamer-based technical platform to measure nearly 1000 proteins from the plasma of 64 Parkinson's disease and 30 normal control individuals recruited at the University of Pennsylvania (UPenn). We identified candidate biomarkers differentiating the two groups, then narrowed these candidates by stability selection to an eight-protein panel. This eight-protein panel classified an independent test set of 32 PD and 15 control subjects from UPenn with 91% accuracy. Furthermore, these same eight proteins differentiated PD individuals from a cohort of 25 AD individuals with >90% accuracy as well. Together, our preliminary findings suggest that a blood test based on just eight plasma proteins has the potential to serve as a confirmatory diagnostic test for PD. While our preliminary work already contains a replication (as we have employed a training/test set design to avoid over-fitting of data), we seek further replication in national or international cohorts of patients recruited outside of our university. This will allow us to understand the generalizability of our findings and pave the way for clinical development of a blood test to confirm PD diagnosis. To do this, we propose three specific aims: (1) To evaluate the robustness of candidate proteins nominated in UPenn subjects through the Somalogic platform. We will do this through (a) the analysis of 38 quality control samples using the aptamer-based array, (b) the analysis of duplicate aliquots of 30-50 samples previously investigated on the Somalogic panel, using a mass spectrometry-based approach to quantitative proteomics. (2) To repeat the aptamer-based screen on 319 samples from the Parkinson's Disease Biomarker Program biorepository, representing PD as well as controls, with both PD and controls originating from two clinical sites. Using our existing data, as well as the PDBP data, we will determine whether our 8-marker panel can reproducibly identify PD samples. (3) To test a small panel of proteins that pass quality control in Aim 1 and are replicated in Aim 2, using alternative, low-cost assays, in 450 samples from PPMI.

Goals

Goals of this project:

1. Longitudinal PDBP plasma samples will be used for analysis on the SomaSCAN platform to develop a classifying panel for disease diagnosis and progression.

2. Replicate panel using mass spectrometry approach.

Available Data Types