Article type: Research Article
Authors: Trupp, Miles | Jonsson, Pär | Öhrfelt, Annika | Zetterberg, Henrik; | Obudulu, Ogonna | Malm, Linus | Wuolikainen, Anna | Linder, Jan | Moritz, Thomas | Blennow, Kaj | Antti, Henrik | Forsgren, Lars
Affiliations: Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå, Sweden | Department of Chemistry, Umeå University, Umeå, Sweden | Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden | UCL Institute of Neurology, Queen Square, London, UK | Swedish Metabolomics Centre, Department of Plant Physiology and Forest Genetics, Swedish Agricultural University, Umeå, Sweden
Note: [] Correspondence to: Miles Trupp, Department of Pharmacology and Clinical Neuroscience/Neurology, Umeå University, SE-90185, Umeå, Sweden. E-mail: [email protected]
Abstract: Background: Parkinson's disease (PD) is a progressive, multi-focal neurodegenerative disease for which there is no effective disease modifying treatment. A critical requirement for designing successful clinical trials is the development of robust and reproducible biomarkers identifying PD in preclinical stages. Objective: To investigate the potential for a cluster of biomarkers visualized with multiple analytical platforms to provide a clinically useful tool. Methods: Gas Chromatography-Mass Spectrometry (GC-TOFMS) based metabolomics and immunoassay-based protein/peptide analyses on samples from patients with PD diagnosed in Northern Sweden. Low molecular weight compounds from both plasma and cerebrospinal fluid (CSF) from 20 healthy subjects (controls) and 20 PD patients at the time of diagnosis (baseline) were analyzed. Results: In plasma, we found a significant increase in several amino acids and a decrease in C16-C18 saturated and unsaturated fatty acids in patients as compared to control subjects. We also observed an increase in plasma levels of pyroglutamate and 2-oxoisocaproate (ketoleucine) that may be indicative of increased metabolic stress in patients. In CSF, there was a generally lower level of metabolites in PD as compared to controls, with a specific decrease in 3-hydroxyisovaleric acid, tryptophan and creatinine. Multivariate analysis and modeling of metabolites indicates that while the PD samples can be separated from control samples, the list of detected compounds will need to be expanded in order to define a robust predictive model. CSF biomarker immunoassays of candidate peptide/protein biomarkers revealed a significant decrease in the levels of Aβ-38 and Aβ-42, and an increase in soluble APPα in CSF of patients. Furthermore, these peptides showed significant correlations to each other, and positive correlations to the CSF levels of several 5- and 6-carbon sugars. However, combining these metabolites and proteins/peptides into a single model did not significantly improve the statistical analysis. Conclusions: Together, this metabolomics study has detected significant alterations in plasma and CSF levels of a cluster of amino acids, fatty acids and sugars based on clinical diagnosis and levels of known protein and peptide biomarkers.
Keywords: Parkinson's, CSF, metabolomics, Abeta peptides, alpha-synuclein, GC-TOFMS, multivariate analysis, amino acids, long-chain fatty acids, carbohydrates
DOI: 10.3233/JPD-140389
Journal: Journal of Parkinson's Disease, vol. 4, no. 3, pp. 549-560, 2014
