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Metabolomic investigations in cerebrospinal fluid of Parkinson's disease


Willkommen, Desiree; Lucio, Marianna; Moritz, Franco; Forcisi, Sara; Kanawati, Basem; Smirnov, Kirill S; Schroeter, Michael; Sigaroudi, Ali; Schmitt-Kopplin, Philippe; Michalke, Bernhard (2018). Metabolomic investigations in cerebrospinal fluid of Parkinson's disease. PLoS ONE, 13(12):e0208752.

Abstract

The underlying mechanisms of Parkinson´s disease are not completely revealed. Especially, early diagnostic biomarkers are lacking. To characterize early pathophysiological events, research is focusing on metabolomics. In this case-control study we investigated the metabolic profile of 31 Parkinson´s disease-patients in comparison to 95 neurologically healthy controls. The investigation of metabolites in CSF was performed by a 12 Tesla SolariX Fourier transform-ion cyclotron resonance-mass spectrometer (FT-ICR-MS). Multivariate statistical analysis sorted the most important biomarkers in relation to their ability to differentiate Parkinson versus control. The affected metabolites, their connection and their conversion pathways are described by means of network analysis. The metabolic profiling by FT-ICR-MS in CSF yielded in a good group separation, giving insights into the disease mechanisms. A total number of 243 metabolites showed an affected intensity in Parkinson´s disease, whereas 15 of these metabolites seem to be the main biological contributors. The network analysis showed a connection to the tricarboxylic cycle (TCA cycle) and therefore to mitochondrial dysfunction and increased oxidative stress within mitochondria. The metabolomic analysis of CSF in Parkinson´s disease showed an association to pathways which are involved in lipid/ fatty acid metabolism, energy metabolism, glutathione metabolism and mitochondrial dysfunction.

Abstract

The underlying mechanisms of Parkinson´s disease are not completely revealed. Especially, early diagnostic biomarkers are lacking. To characterize early pathophysiological events, research is focusing on metabolomics. In this case-control study we investigated the metabolic profile of 31 Parkinson´s disease-patients in comparison to 95 neurologically healthy controls. The investigation of metabolites in CSF was performed by a 12 Tesla SolariX Fourier transform-ion cyclotron resonance-mass spectrometer (FT-ICR-MS). Multivariate statistical analysis sorted the most important biomarkers in relation to their ability to differentiate Parkinson versus control. The affected metabolites, their connection and their conversion pathways are described by means of network analysis. The metabolic profiling by FT-ICR-MS in CSF yielded in a good group separation, giving insights into the disease mechanisms. A total number of 243 metabolites showed an affected intensity in Parkinson´s disease, whereas 15 of these metabolites seem to be the main biological contributors. The network analysis showed a connection to the tricarboxylic cycle (TCA cycle) and therefore to mitochondrial dysfunction and increased oxidative stress within mitochondria. The metabolomic analysis of CSF in Parkinson´s disease showed an association to pathways which are involved in lipid/ fatty acid metabolism, energy metabolism, glutathione metabolism and mitochondrial dysfunction.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Clinical Pharmacology and Toxicology
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > General Biochemistry, Genetics and Molecular Biology
Life Sciences > General Agricultural and Biological Sciences
Health Sciences > Multidisciplinary
Uncontrolled Keywords:General Biochemistry, Genetics and Molecular Biology, General Agricultural and Biological Sciences, General Medicine
Language:English
Date:10 December 2018
Deposited On:31 Jan 2019 12:38
Last Modified:20 Jun 2024 01:36
Publisher:Public Library of Science (PLoS)
ISSN:1932-6203
OA Status:Gold
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1371/journal.pone.0208752
PubMed ID:30532185
  • Content: Published Version
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)