Urinary Metabolomics on the Biochemical Profiles in Diet-Induced Hyperlipidemia Rat Using Ultraperformance Liquid Chromatography Coupled with Quadrupole Time-of-Flight SYNAPT High-Definition Mass Spectrometry.

Hua Miao,Lu Yin,Xu Bai,Xian-Long Cheng,Xu Zhang,Dan-Qian Chen,Hua Chen,Feng Wei

doi:10.1155/2014/184162

Abstract

Ultraperformance liquid chromatography coupled with quadrupole time-of-flight synapt high-definition mass spectrometry metabolomics was used to characterize the urinary metabolic profiling of diet-induced hyperlipidaemia in a rat model. Analysis was done by orthogonal partial least squares discriminant analysis, correlation analysis, heat map analysis, and KEGG pathways analysis. Potential biomarkers were chosen by S-plot and were identified by accurate mass, isotopic pattern, and MS/MS fragments information. Significant differences in fatty acid, amino acid, nucleoside, and bile acid were observed, indicating the perturbations of fatty acid, amino acid, nucleoside, and bile acid metabolisms in diet-induced hyperlipidaemia rats. This study provides further insight into the metabolic profiling across a wide range of biochemical pathways in response to diet-induced hyperlipidaemia.

Highlights

Metabolomics is the quantitative measurement of the dynamic multiparametric metabolic responses of living systems to pathophysiological stimuli or genetic modifications [1]
The previous study demonstrated that urinary citric acid was significantly decreased in diet-induced hyperlipidemia [9]. These results indicated that amino acids metabolism and TCA cycle were disturbed in diet-induced hyperlipidemia rats
Urinary metabolomics based on ultraperformance liquid chromatography (UPLC) Q-TOF/HDMS, a novel mass spectrometryElevatedEnergy (MSE) data collection technique, and a multivariate statistical technique has been used to study diet-induced hyperlipidaemia in a rat model

Summary

Introduction

Metabolomics is the quantitative measurement of the dynamic multiparametric metabolic responses of living systems to pathophysiological stimuli or genetic modifications [1]. As a powerful analytical platform, the application of metabolomics has dramatically increased in the fields of physiological evaluation, disease diagnosis, disease prognosis, therapy, biomarker discovery, drug therapy monitoring, and safety and toxicity evaluation [3]. Hyperlipidaemia, as a major risk factor of coronary heart disease, is one of the most important public health problems, with increasing rates of incidence and prevalence [4]. As a progressive chronic and metabolic disease, cardiovascular disease begins in adult and progresses to morbidity and mortality throughout the lifespan. Hyperlipidaemia has an important effect on development and progression of various cardiovascular diseases and atherosclerosis.

Methods

Results

Conclusion