A Multiplatform Metabolomics Approach to Characterize Plasma Levels of Phenylalanine and Tyrosine in Phenylketonuria
Background: Different pathophysiological mechanisms have been described in phenylketonuria (PKU) but the indirect metabolic consequences of metabolic disorders caused by elevated Phe or low Tyr concentrations remain partially unknown. We used a multiplatform metabolomics approach to evaluate the metabolic signature associated with Phe and Tyr.
Material and methods: We prospectively included 10 PKU adult patients and matched controls. We analysed the metabolome profile using GC-MS (urine), amino-acid analyzer (urine and plasma) and nuclear magnetic resonance spectroscopy (urine). We performed a multivariate analysis from the metabolome (after exclusion of Phe, Tyr and directly derived metabolites) to explain plasma Phe and Tyr concentrations, and the clinical status. Finally, we performed a univariate analysis of the most discriminant metabolites and we identified the associated metabolic pathways.
Results: We obtained a metabolic pattern from 118 metabolites and we built excellent multivariate models to explain Phe, Tyr concentrations and PKU diagnosis. Common metabolites of these models were identified: Gln, Arg, succinate and alpha aminobutyric acid. Univariate analysis showed an inverse correlation between Arg, alpha aminobutyric acid and Phe and a positive correlation between Arg, succinate, Gln and Tyr (p < 0.0003). Thus, we highlighted the following pathways: Arg and Pro, Ala, Asp and Glu metabolism.
Discussion: We obtain a specific metabolic signature related to Tyr and Phe concentrations. We confirmed the involvement of different pathophysiological mechanisms previously described in PKU such as protein synthesis, energetic metabolism and oxidative stress. The metabolomics approach is relevant to explore PKU pathogenesis.
KeywordsBiomarkers Metabolomics NMR Phenylketonuria
- 1H NMR
Nuclear magnetic resonance
- CV ANOVA
ANalysis Of VAriance testing of cross validated predictive residuals, used to evaluate the robustness of multivariate model
Gas chromatography coupled with mass spectrometry
Hierarchical cluster analysis
A web metabolomics tool to analyse metabolic pathways
Orthogonal partial least-squares discriminant analysis
Partial least square
Parameter to estimate of the predictive ability of the model, used to evaluate the robustness of multivariate model
Parameter defined as a fraction of the variance explained by a component, used to evaluate the robustness of multivariate model
- UV Scaling
UV scaling is defined by a variable that is centred and scaled to “Unit Variance”, i.e. the base weight is computed as 1/SD, where SD is the standard deviation of variable computed around the mean.
Variable importance parameters
The authors would like to thank Hervé Meudal (Centre de Biophysique Moléculaire Orleans) for technical assistance with NMR spectrometer, and Colette Faideau, Stéphanie Premeau, Ghislaine Bruneau and Laurence Saison for their technical help.
This study was funded by the Hospital of Tours.
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