Urinary and plasma metabolite differences detected by HPLC-ESI-QTOF-MS in systemic sclerosis patients

PRECISESADS Clinical Consortium, Álvaro Fernández-Ochoa, Rosa Quirantes-Piné, Isabel Borrás-Linares, David Gemperline, Marta E. Alarcón Riquelme, Lorenzo Beretta, Antonio Segura-Carretero

Research output: Contribution to journalArticlepeer-review


Systemic Sclerosis (SSc) is a chronic autoimmune disease whose origin and pathogenesis are not yet well known. Recent studies are allowing a better definition of the disease. However, few studies have been performed based on metabolomics. In this way, this study aims to find altered metabolites in SSc patients in order to improve their diagnosis, prognosis and treatment. For that, 59 SSc patients and 28 healthy volunteers participated in this study. Urine and plasma samples were analysed by a fingerprinting metabolomic approach based on HPLC-ESI-QTOF-MS. We observed larger differences in urine than plasma metabolites. The main deregulated metabolic families in urine were acylcarnitines, acylglycines and metabolites derived from amino acids, specifically from proline, histidine and glutamine. These results indicate perturbations in fatty acid beta oxidation and amino acid pathways in scleroderma patients. On the other hand, the main plasma biomarker candidate was 2-arachidonoylglycerol, which is involved in the endocannabinoid system with potential implications in the induction and propagation of systemic sclerosis and autoimmunity.

Original languageEnglish
Pages (from-to)82-90
Number of pages9
JournalJournal of Pharmaceutical and Biomedical Analysis
Publication statusPublished - Jan 5 2019


  • 2-arachidonoylglycerol
  • Acylcarnitines
  • Biomarker
  • Metabolomics
  • Systemic sclerosis

ASJC Scopus subject areas

  • Analytical Chemistry
  • Pharmaceutical Science
  • Drug Discovery
  • Spectroscopy
  • Clinical Biochemistry


Dive into the research topics of 'Urinary and plasma metabolite differences detected by HPLC-ESI-QTOF-MS in systemic sclerosis patients'. Together they form a unique fingerprint.

Cite this