Identification of essential hypertension biomarkers in human urine by non-targeted metabolomics based on UPLC-Q-TOF/MS

Clin Chim Acta. 2018 Nov:486:192-198. doi: 10.1016/j.cca.2018.08.006. Epub 2018 Aug 7.

Abstract

Background: In recent years, using metabolomics technology to study hypertension has made some progress. However, in actual clinical studies, there are few studies on hypertension related metabonomics with human urine as samples. In this study, the urine samples of patients with essential hypertension (EH) were studied by comparing with healthy people to explore the changes of urine metabolites between hypertensive patients and healthy people in order to find potential biomarkers and metabolic pathways.

Methods: An ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology was used to analyze the urine metabolites of 75 cases of essential hypertension group (EH) and 75 cases of healthy control group (HC).

Results: According to the PLS-DA pattern recognition analysis, substances with significant differences (P < .05) between the EH group and the HC group were screened out, including 10 potential biomarkers such as L-methionine. The metabolic pathways involved were amino acid metabolism, fatty acid metabolism steroid hormone, biosynthesis and oxidative stress.

Conclusion: The non-targeted metabolomics based on UPLC-Q-TOF/MS technology can effectively identify the differential metabolites of potential biomarkers in the urine of essential hypertensive patients and provide a theoretical basis for the treatment of clinical hypertension.

Keywords: Essential hypertension; Markers; Metabolomics; UPLC-Q-TOF/MS; Urine.

Publication types

  • Clinical Trial

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Biomarkers / metabolism
  • Biomarkers / urine*
  • Case-Control Studies
  • Chromatography, High Pressure Liquid
  • Essential Hypertension / metabolism
  • Essential Hypertension / urine*
  • Humans
  • Mass Spectrometry
  • Metabolomics*
  • Middle Aged
  • Software
  • Young Adult

Substances

  • Biomarkers