High-Throughput Metabolomics for Discovering Potential Metabolite Biomarkers and Metabolic Mechanism from the APPswe/PS1dE9 Transgenic Model of Alzheimer's Disease.

ABSTRACT

Alzheimer's disease (AD), a neurodegenerative disorder, is the major form of dementia. As AD is an irreversible disease, it is necessary to focus on earlier intervention. However, the potential biomarkers of preclinical AD are still not clear. In this study, urinary metabolomics based on ultra-high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry was performed for delineating the metabolic changes and potential early biomarkers in APPswe/PS1dE9 (APP/PS1) transgenic mice. A total of 24 differentially regulated metabolites were identified when comparing transgenic mice to wild-type mice using multivariate statistical analysis. Among them, 10 metabolites were significantly upregulated and 14 metabolites were downregulated. On the basis of these potential biomarkers, metabolic pathway analysis found that pentose and glucuronate interconversions, glyoxylate and dicarboxylate metabolism, starch and sucrose metabolism, the citrate cycle, tryptophan metabolism, and arginine and proline metabolism were disturbed in APP/PS1 mice. Our study revealed that levels of endogenous metabolites in the urine of APP/PS1 mice changed prior to the emergence of learning and cognitive impairment, which may be associated with abnormal nitric oxide production pathways and metabolic disorders of monoaminergic neurotransmitters. In conclusion, this study showed that metabolomics provides an early indicator of disease occurrence for AD.