Session Information
Date: Thursday, June 8, 2017
Session Title: Parkinson’s Disease: Clinical Trials, Pharmacology And Treatment
Session Time: 1:15pm-2:45pm
Location: Exhibit Hall C
Objective: To employ a combination of elemental concentrations in the cerebrospinal fluid (CSF) to identify a diagnostic biomarker profile differentiating patients with idiopathic Parkinson´s disease (PD) and age-matched controls.
Background: The diagnosis of PD, particularly in early disease stages, remains challenging and is mostly based on clinical features. Several elements, including transition metals, have been implied in the pathogenesis of PD. Due to its close spatial relation with the brain parenchyma, CSF reflects pathophysiological alterations occurring in neurodegeneration, and its examination is part of the diagnostic routine.
Methods: Patients with the diagnosis of PD and age-matched controls were clinically characterized and CSF was collected according to standardized protocols. CSF samples were subjected to inductively-coupled plasma-sectorfield-mass spectrometry (ICP-sf-MS) for detection of elemental profiles, and machine learning algorithms were applied to classify patients based on the abundance of elements in CSF.
Results: We analyzed a total of 82 CSF samples (PD: n= 39; age-matched controls: n= 43) resolving 29 single elements. Within a 10 times 10-fold cross validation the extreme gradient boosting algorithm achieved an area under the ROC curve of .84, when including data for the abundance of 19 elements. The consensus specificity/sensitivity across the 10 repeats at the Youden index was 78.6% and 83.3%, respectively. The training data was re-classified to 100% by the algorithm.
Conclusions: Our study demonstrates that elemental concentrations in CSF obtained by ICP-MS can be used as fingerprint allowing to correctly classify PD patients and age-matched controls. To validate these results and to evaluate the usefulness of this technique in the differentiation from atypical Parkinsonism further analyses are currently ongoing.
To cite this abstract in AMA style:
P. Lingor, A. Leha, B. Michalke, M. Börger, M. Bähr, I. Zerr, F. Maass. Elemental fingerprint as a cerebrospinal fluid biomarker for the diagnosis of Parkinson’s disease [abstract]. Mov Disord. 2017; 32 (suppl 2). https://www.mdsabstracts.org/abstract/elemental-fingerprint-as-a-cerebrospinal-fluid-biomarker-for-the-diagnosis-of-parkinsons-disease/. Accessed May 13, 2025.« Back to 2017 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/elemental-fingerprint-as-a-cerebrospinal-fluid-biomarker-for-the-diagnosis-of-parkinsons-disease/