Background: As a recognized risk factor for cardiovascular disease (CVD), hyperlipidemia (HLP) has developed into a high incidence disease that seriously threatens human health. Finding a new target for effective treatment of HLP will be a powerful way to reduce the incidence of CVD. The purpose of this study was to find potential biomarkers in urine of HLP patients and analyze their metabolic pathways to study the pathogenesis of HLP.
Methods: An UPLC-Q-TOF/MS technology was used to detect the metabolites in urine of 60 HLP patients and 60 normal controls. Based on PLS-DA pattern recognition, potential biomarkers related to HLP were screened out.
Results: 22 potential biomarkers related to HLP were identified, which involved amino acid metabolism, fatty acid metabolism, nucleotide metabolism, steroid hormone metabolism and intestinal flora metabolism, and their possible pathogenesis was found to be related to inflammatory reaction and oxidative stress.
Conclusion: The non-targeted metabolomic method based on UPLC-Q-TOF/MS technology can effectively identify potential biomarkers in the urine of HLP patients and explore the possible pathogenesis. Our research will lay a foundation for finding new targets for the treatment of HLP and provide a basis for clinical research on the treatment of HLP.
Keywords: Biomarkers; Hyperlipidemia; Metabolomics; Pathogenesis; UPLC-Q-TOF/MS.
Copyright © 2019. Published by Elsevier B.V.