Journal
JOURNAL OF PROTEOME RESEARCH
Volume 17, Issue 7, Pages 2460-2469Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.8b00224
Keywords
prodromal Parkinson's disease; metabolomics; mass spectrometry; NMR; biomarkers
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Funding
- Fred A. & Barbara M. Erb Foundation
- Peter C. and Emajean Cook Foundation
- National Institutes of Health [1R01DC016519-01, 5R21NS09399302]
- NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R21NS093993] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE ON DEAFNESS AND OTHER COMMUNICATION DISORDERS [R01DC016519] Funding Source: NIH RePORTER
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Parkinson's disease is the second most common neurodegenerative disease. In the vast majority of cases the origin is not genetic and the cause is not well understood, although progressive accumulation of alpha-synuclein aggregates appears central to the pathogenesis. Currently, treatments that slow disease progression are lacking, and there are no robust biomarkers that can facilitate the development of such treatments or act as aids in early diagnosis. Therefore, we have defined metabolomic changes in the brain and serum in an animal model of prodromal Parkinson's disease. We biochemically profiled the brain tissue and serum in a mouse model with progressive synucleinopathy propagation in the brain triggered by unilateral injection of preformed alpha-synuclein fibrils in the olfactory bulb. In total, we accurately identified and quantified 71 metabolites in the brain and 182 in serum using NMR and targeted mass spectrometry, respectively. Using multivariate analysis, we accurately identified which metabolites explain the most variation between cases and controls. Using pathway enrichment analysis, we highlight significantly perturbed biochemical pathways in the brain and correlate these with the progression of the disease. Furthermore, we identified the top six discriminatory metabolites and were able to develop a model capable of identifying animals with the pathology from healthy controls with high accuracy (AUC (95% CI) = 0.861 (0.755-0.968)). Our study highlights the utility of metabolomics in identifying elements of Parkinson's disease pathogenesis and for the development of early diagnostic biomarkers of the disease.
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