Jean-Pierre Trezzi1,2, Sara Galozzi3, Christian Jaeger1, Katalin Barkovits3, Kathrin Brockmann4,5, Walter Maetzler4,5, Daniela Berg4,5,6, Katrin Marcus3, Fay Betsou2, Karsten Hiller1,7,8, Brit Mollenhauer9,10. 1. Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Luxembourg, Luxembourg. 2. Integrated Biobank of Luxembourg, Luxembourg, Luxembourg. 3. Functional Proteomics, Medizinisches Proteom-Center, Ruhr-University Bochum, Bochum, Germany. 4. Department of Neurodegenerative Diseases and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany. 5. German Center for Neurodegenerative Diseases, Tübingen, Germany. 6. Department of Neurology, Christian-Albrechts-University, Kiel, Germany. 7. Braunschweig Integrated Centre of Systems Biology, University of Braunschweig, Braunschweig, Germany. 8. Department of Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany. 9. Paracelsus-Elena Klinik, Kassel, Germany. 10. University Medical Center Goettingen, Institute of Neuropathology and Department of Neurosurgery, Goettingen, Germany.
Abstract
OBJECTIVE: The purpose of this study was to profile cerebrospinal fluid (CSF) from early-stage PD patients for disease-related metabolic changes and to determine a robust biomarker signature for early-stage PD diagnosis. METHODS: By applying a non-targeted and mass spectrometry-driven approach, we investigated the CSF metabolome of 44 early-stage sporadic PD patients yet without treatment (DeNoPa cohort). We compared all detected metabolite levels with those measured in CSF of 43 age- and gender-matched healthy controls. After this analysis, we validated the results in an independent PD study cohort (Tübingen cohort). RESULTS: We identified that dehydroascorbic acid levels were significantly lower and fructose, mannose, and threonic acid levels were significantly higher (P < .05) in PD patients when compared with healthy controls. These changes reflect pathological oxidative stress responses, as well as protein glycation/glycosylation reactions in PD. Using a machine learning approach based on logistic regression, we successfully predicted the origin (PD patients vs healthy controls) in a second (n = 18) as well as in a third and completely independent validation set (n = 36). The biomarker signature is composed of the three markers-mannose, threonic acid, and fructose-and allows for sample classification with a sensitivity of 0.790 and a specificity of 0.800. CONCLUSION: We identified PD-specific metabolic changes in CSF that were associated with antioxidative stress response, glycation, and inflammation. Our results disentangle the complexity of the CSF metabolome to unravel metabolome changes related to early-stage PD. The detected biomarkers help understanding PD pathogenesis and can be applied as biomarkers to increase clinical diagnosis accuracy and patient care in early-stage PD.
OBJECTIVE: The purpose of this study was to profile cerebrospinal fluid (CSF) from early-stage PDpatients for disease-related metabolic changes and to determine a robust biomarker signature for early-stage PD diagnosis. METHODS: By applying a non-targeted and mass spectrometry-driven approach, we investigated the CSF metabolome of 44 early-stage sporadic PDpatients yet without treatment (DeNoPa cohort). We compared all detected metabolite levels with those measured in CSF of 43 age- and gender-matched healthy controls. After this analysis, we validated the results in an independent PD study cohort (Tübingen cohort). RESULTS: We identified that dehydroascorbic acid levels were significantly lower and fructose, mannose, and threonic acid levels were significantly higher (P < .05) in PDpatients when compared with healthy controls. These changes reflect pathological oxidative stress responses, as well as protein glycation/glycosylation reactions in PD. Using a machine learning approach based on logistic regression, we successfully predicted the origin (PDpatients vs healthy controls) in a second (n = 18) as well as in a third and completely independent validation set (n = 36). The biomarker signature is composed of the three markers-mannose, threonic acid, and fructose-and allows for sample classification with a sensitivity of 0.790 and a specificity of 0.800. CONCLUSION: We identified PD-specific metabolic changes in CSF that were associated with antioxidative stress response, glycation, and inflammation. Our results disentangle the complexity of the CSF metabolome to unravel metabolome changes related to early-stage PD. The detected biomarkers help understanding PD pathogenesis and can be applied as biomarkers to increase clinical diagnosis accuracy and patient care in early-stage PD.
Authors: Desiree Willkommen; Marianna Lucio; Franco Moritz; Sara Forcisi; Basem Kanawati; Kirill S Smirnov; Michael Schroeter; Ali Sigaroudi; Philippe Schmitt-Kopplin; Bernhard Michalke Journal: PLoS One Date: 2018-12-10 Impact factor: 3.240
Authors: Daniel Stoessel; Claudia Schulte; Marcia C Teixeira Dos Santos; Dieter Scheller; Irene Rebollo-Mesa; Christian Deuschle; Dirk Walther; Nicolas Schauer; Daniela Berg; Andre Nogueira da Costa; Walter Maetzler Journal: Front Aging Neurosci Date: 2018-03-05 Impact factor: 5.750