4.8 Article

Metabolic profiling reveals new serum signatures to discriminate lupus nephritis from systemic lupus erythematosus

Journal

FRONTIERS IN IMMUNOLOGY
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2022.967371

Keywords

systemic lupus erythematosus; lupus nephritis; non-targeted metabonomics; high performance liquid chromatography tandem mass spectrometry; serum signatures

Categories

Funding

  1. medical science and technology project of Health Committee of Sichuan Province [21PJ176]
  2. Popularized application projects of Health Committee of Sichuan Province [20PJ256]
  3. Youth Innovation Research Project of Sichuan Medical Association [Q21012]
  4. Hospital-level project of Mianyang Central Hospital [2020YJ02]

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This study utilized a metabolomics approach to identify five serum metabolites that have the potential to serve as indicators for the differential diagnosis of SLE and LN. Glycerolphospholipid metabolism may play a crucial role in the development of SLE into LN.
BackgroundLupus nephritis (LN) occurs in 50% of patients with systemic lupus erythematosus (SLE), causing considerable morbidity and even mortality. Previous studies had shown the potential of metabolic profiling in the diagnosis of SLE or LN. However, few metabonomics studies have attempted to distinguish SLE from LN based on metabolic changes. The current study was designed to find new candidate serum signatures that could differentiate LN from SLE patients using a non-targeted metabonomics method based on ultra high performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). MethodMetabolic profiling of sera obtained from 21 healthy controls, 52 SLE patients and 43 LN patients. We used SPSS 25.0 for statistical analysis. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and metabolic pathway analysis were used to analyze the metabolic data. ResultsUpon comparison of SLE and LN groups, 28 differential metabolites were detected, the majority of which were lipids and amino acids. Glycerolphospholipid metabolism, pentose and glucuronate interconversions and porphyrin and chlorophyll metabolism were obviously enriched in LN patients versus those with SLE. Among the 28 characteristic metabolites, five key serum metabolites including SM d34:2, DG (18:3(9Z,12Z,15Z)/20:5(5Z,8Z,11Z,14Z,17Z)/0:0), nervonic acid, Cer-NS d27:4, and PC (18:3(6Z,9Z,12Z)/18:3(6Z,9Z,12Z) performed higher diagnostic performance in discriminating LN from SLE (all AUC > 0.75). Moreover, combined analysis of neuritic acid, C1q, and CysC (AUC = 0.916) produced the best combined diagnosis. ConclusionThis study identified five serum metabolites that are potential indicators for the differential diagnosis of SLE and LN. Glycerolphospholipid metabolism may play an important role in the development of SLE to LN. The metabolites we screened can provide more references for the diagnosis of LN and more support for the pathophysiological study of SLE progressed to LN.

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