Abstract :
[en] 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 (T€ubingen 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
(n518) as well as in a third and completely independent
validation set (n536). 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 earlystage
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.
Scopus citations®
without self-citations
72