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PO.1.7 Urinary metabolomic profile of systemic lupus erythematosus and lupus nephritis based on liquid and gas chromatography/mass spectrometry (LC-QTOF-MS and GC-QTOF-MS)
  1. A Rojo Sánchez1,
  2. A Carmona Marte1,
  3. M Santamaría Torres2,
  4. Y Díaz Olmos3,
  5. G Aroca Martínez4,
  6. E Navarro Quiroz5,
  7. M Cala Molina2 and
  8. L Pacheco Lugo5
  1. 1Universidad Simón Bolívar ~ Barranquilla ~ Colombia
  2. 2MetCore – Metabolomics Core Facility. Vice-Presidency for Research, Universidad de los Andes ~ Bogotá ~ Colombia
  3. 3División Ciencias de la Salud. Departamento de Medicina. Universidad del Norte. ~ Barranquilla ~ Colombia
  4. 4Clínica de la Costa ~ Barranquilla ~ Colombia
  5. 5Facultad de Ciencias Básicas y Biomédicas. Universidad Simón Bolívar. ~ Barranquilla ~ Colombia


Purpose Systemic lupus erythematosus (SLE or lupus) is a chronic autoimmune disease, and kidney involvement with SLE, lupus nephritis (LN), is a frequent and severe complication of SLE that increases patient morbidity and mortalityis. The current gold standard for classifying LN progression is a renal biopsy, an invasive procedure with potential risks. Undergoing a series of biopsies for monitoring disease progression and treatments is unlikely suitable for patients with LN. Thus, there is an urgent need for non-invasive alternative biomarkers that can facilitate LN class diagnosis. Such biomarkers will be very useful in guiding intervention strategies to mitigate or treat patients with LN. The current study aims to explore new biomarker candidates for non-invasive diagnosis of LN and explore the pathogenic mechanisms that contribute to renal injury.

Materials and Methods A metabolomics approach using LC-QTOF-MS in both positive and negative electrospray ionization (ESI) modes and GC-QTOF-MS was developed for comparison of urine metabolic profile of 23 LN patients, 16 SLE patients, and 10 healthy controls (HCs). Differential metabolites were evaluated with univariate (UVA) and multivariate (MVA) analysis using a nonparametric t test, principal component analysis (PCA) and orthogonal partial least squares regression (OPLS-DA).

Results Both UVA and MVA showed a clear discrimination in the urinary metabolome between LN, SLE and HCs. The significant altered metabolites between LN and SLE correspond mainly to fatty acyls, amino acids, bile acids in particular methylglutamic acid, monopalmitin methyl-L-proline, 3-oxo-4-pentenoic acid, glutaric acid, 3-hydroxyglutaric acid, citraconic acid, glutamine, glycocholic acid and ureidoisobutyric acid. Analysis of metabolic pathways shows disturbances in biosynthesis of alanine, aspartate and glutamate metabolism, citrate cycle (TCA cycle) and glutamine and glutamate metabolism.

Conclusions The urinary metabolome of SLE and LN patients made it possible to determine metabolic alterations and discriminate LN patients from SLE patients. If confirmed in larger studies, these urine metabolites may serve as biomarkers to help discriminate between SLE with and without renal involvement.

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