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.
Currently, the need for biomarkers in PD is great, but truly useful biomarkers need to be robust to multiple sources of variability, as evidenced by successful large-scale replication. Using samples from 166 patients from the University of Pennsylvania, we have discovered an eight-protein panel of plasma proteins that discriminates PD from control samples with high accuracy. The studies proposed here seek to move this eight-protein panel within striking distance of clinical translation through replication in the Parkinson's Disease Biomarker Program cohort, followed by the Parkinson's Progression Marker Initiative cohort. If successful, they could pave the way for a blood test for PD confirmation.
| Chen-Plotkin, Alice S; Albin, Roger; Alcalay, Roy et al. (2018) Finding useful biomarkers for Parkinson's disease. Sci Transl Med 10: |
| Tropea, Thomas F; Chen-Plotkin, Alice S (2018) Unlocking the mystery of biomarkers: A brief introduction, challenges and opportunities in Parkinson Disease. Parkinsonism Relat Disord 46 Suppl 1:S15-S18 |
| Chen-Plotkin, Alice S; Zetterberg, Henrik (2018) Updating Our Definitions of Parkinson's Disease for a Molecular Age. J Parkinsons Dis 8:S53-S57 |
| Gallagher, Michael D; Chen-Plotkin, Alice S (2018) The Post-GWAS Era: From Association to Function. Am J Hum Genet 102:717-730 |
| Tropea, Thomas F; Xie, Sharon X; Rick, Jacqueline et al. (2018) APOE, thought disorder, and SPARE-AD predict cognitive decline in established Parkinson's disease. Mov Disord 33:289-297 |
| Chen-Plotkin, Alice S (2018) Parkinson disease: Blood transcriptomics for Parkinson disease? Nat Rev Neurol 14:5-6 |
| Deck, Benjamin L; Rick, Jacqueline; Xie, Sharon X et al. (2017) Statins and Cognition in Parkinson's Disease. J Parkinsons Dis 7:661-667 |
| Liu, Ganqiang; Locascio, Joseph J; Corvol, Jean-Christophe et al. (2017) Prediction of cognition in Parkinson's disease with a clinical-genetic score: a longitudinal analysis of nine cohorts. Lancet Neurol 16:620-629 |
| Akhtar, Rizwan S; Xie, Sharon X; Chen, Yin J et al. (2017) Regional brain amyloid-? accumulation associates with domain-specific cognitive performance in Parkinson disease without dementia. PLoS One 12:e0177924 |
| Fullard, Michelle E; Xie, Sharon X; Marek, Ken et al. (2017) Vitamin D in the Parkinson Associated Risk Syndrome (PARS) study. Mov Disord 32:1636-1640 |
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