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3‐hydroxykynurenine and other Parkinson's disease biomarkers discovered by metabolomic analysis
Author(s) -
LeWitt Peter A.,
Li Jia,
Lu Mei,
Beach Thomas G.,
Adler Charles H.,
Guo Lining
Publication year - 2013
Publication title -
movement disorders
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.352
H-Index - 198
eISSN - 1531-8257
pISSN - 0885-3185
DOI - 10.1002/mds.25555
Subject(s) - metabolomics , cerebrospinal fluid , parkinson's disease , glutathione , pathogenesis , disease , medicine , biology , chemistry , bioinformatics , biochemistry , enzyme
Parkinson's disease (PD) biomarkers are needed to enhance therapeutics research and to understand PD pathogenesis. Methods that simultaneously measure hundreds of small molecular‐weight compounds—metabolomic analysis–“fingerprint” disease‐specific alterations in individual compounds or metabolic pathways. Beyond a nontargeted search for PD biomarkers, we hypothesized that PD cerebrospinal fluid would show increased formation of the excitotoxin 3‐hydroxykynurenine and diminished concentration of the antioxidant glutathione. Cerebrospinal fluid was collected at <4 hours postmortem from 48 pathologically‐verified PD subjects and 57 comparably‐aged controls. Assays involved ultra‐high‐performance liquid and gas chromatography linked to mass spectrometry. We used univariate techniques to determine fold‐changes in concentrations of biochemicals; false‐discovery rates were calculated to exclude spurious findings. Data was modeled using a Support Vector Machine for analyzing compounds selected by Welch's t test. Classification accuracy was determined by cross‐validation. Of 243 structurally‐identified biochemicals,19 compounds differentiated PD from controls at a 20% false‐discovery level. In PD, mean 3‐hydroxykynurenine concentration was increased by one‐third, and mean oxidized glutathione was decreased by 40% (for each, P < .01). Four of the 19 compounds differentiating PD from controls were N‐acetylated amino acids, suggesting a generalized alteration in N‐acetylation activity. The Support Vector Machine classification model distinguished between groups at 83% sensitivity and 91% specificity for the learning data, and at 65% and 79% from cross‐validation. In this study, the first for metabolomic profiling of PD cerebrospinal fluid, we found several novel biomarkers and offer new directions for recognizing disease‐specific biochemical indicators. The findings support involvement of excitotoxicity and oxidative stress in the pathogenesis of PD. © 2013 International Parkinson and Movement Disorder Society