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  Promising Metabolite Profiles in the Plasma and CSF of Early Clinical Parkinson's Disease

Stoessel, D., Schulte, C., Teixeira dos Santos, M. C., Scheller, D., Rebollo-Mesa, I., Deuschle, C., et al. (2018). Promising Metabolite Profiles in the Plasma and CSF of Early Clinical Parkinson's Disease. Frontiers in Aging Neuroscience, 10: 51. doi:10.3389/fnagi.2018.00051.

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Stoessel, D.1, Author           
Schulte, Claudia2, Author
Teixeira dos Santos, Marcia C.2, Author
Scheller, Dieter2, Author
Rebollo-Mesa, Irene2, Author
Deuschle, Christian2, Author
Walther, D.1, Author           
Schauer, Nicolas2, Author
Berg, Daniela2, Author
Nogueira da Costa, Andre2, Author
Maetzler, Walter2, Author
Affiliations:
1BioinformaticsCIG, Infrastructure Groups and Service Units, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753303              
2External Organizations, ou_persistent22              

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 Abstract: Parkinson’s disease (PD) shows high heterogeneity with regard to the underlying molecular pathogenesis involving multiple pathways and mechanisms. Diagnosis is still challenging and rests entirely on clinical features. Thus, there is an urgent need for robust diagnostic biofluid markers. Untargeted metabolomics allows establishing low-molecular compound biomarkers in a wide range of complex diseases by the measurement of various molecular classes in biofluids such as blood plasma, serum, and cerebrospinal fluid (CSF). Here, we applied untargeted high-resolution mass spectrometry to determine plasma and CSF metabolite profiles. We semiquantitatively determined small-molecule levels (≤1.5 kDa) in the plasma and CSF from early PD patients (disease duration 0-4 years; n = 80 and 40, respectively), and sex- and age-matched controls (n = 76 and 38, respectively). We performed statistical analyses utilizing partial least square and random forest analysis with a 70/30 training and testing split approach, leading to the identification of 20 promising plasma and 14 CSF metabolites. These metabolites differentiated the test set with an AUC of 0.8 (plasma) and 0.9 (CSF). Characteristics of the metabolites indicate perturbations in the glycerophospholipid, sphingolipid, and amino acid metabolism in PD, which underscores the high power of metabolomic approaches. Further studies will enable to develop a potential metabolite-based biomarker panel specific for PD.

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Language(s): eng - English
 Dates: 2018
 Publication Status: Issued
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.3389/fnagi.2018.00051
BibTex Citekey: 10.3389/fnagi.2018.00051
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Title: Frontiers in Aging Neuroscience
  Abbreviation : Front Aging Neurosci
Source Genre: Journal
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Publ. Info: Lausanne : Frontiers Research Foundation
Pages: - Volume / Issue: 10 Sequence Number: 51 Start / End Page: - Identifier: ISSN: 1663-4365
CoNE: https://pure.mpg.de/cone/journals/resource/1663-4365