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May 14, 2026PLoS ONE0 citationsOpen Access

Identification of a diagnostic metabolomic fingerprint in plasma for eosinophilic granulomatosis with polyangiitis

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SSSongsen SuYLYanfang Lin

Key Points

  • This work aimed to characterize the plasma metabolomic profiles of patients with eosinophilic granulomatosis with polyangiitis and identify potential biomarkers that differentiate it from bronchial asthma.
  • Enrolled 10 patients with eosinophilic granulomatosis with polyangiitis, 10 with bronchial asthma, and 10 healthy controls.
  • Performed untargeted metabolomics using liquid chromatography/mass spectrometry to analyze plasma.
  • Conducted receiver operating characteristic curve analysis to evaluate diagnostic performance of metabolites.
  • Identified 971 differentially expressed metabolites between EGPA patients and healthy controls with 59 enriched pathways.
  • Found 161 altered metabolites when comparing EGPA to bronchial asthma, with three significant pathways.
  • Demonstrated that 21 of 24 metabolites showed strong diagnostic performance (AUC > 0.8) for distinguishing EGPA from bronchial asthma.

Abstract

Objective Eosinophilic granulomatosis with polyangiitis (EGPA) was a rare systemic vasculitis characterized by eosinophilia, asthma, and necrotizing vasculitis. Metabolic dysregulation had been shown to participate in the pathogenesis of autoimmune diseases, but the plasma metabolic profile of EGPA remained unclear. This work was designed to systematically characterize the plasma metabolomic profiles of EGPA patients, identify differential metabolites that distinguish EGPA from bronchial asthma (BA), and explore their potential as biomarkers for differential diagnosis. Methods Ten patients with EGPA, ten patients with BA, and ten age- and gender-matched healthy controls (HCs) were enrolled. Untargeted metabolomics based on liquid chromatography/mass spectrometry (LC/MS) was performed to analyze the metabolic profiles of the three groups. Differential metabolites were identified using VIP > 1 and P 0.8). Four metabolites (cholesterol, 5-acetylamino-6-formylamino-3-methyluracil, 5-acetylamino-6-amino-3-methyluracil, and 3-methylxanthine) showed high diagnostic potential (AUC > 0.8) for distinguishing EGPA from BA. Conclusion This study revealed, for the first time, a distinct plasma metabolic profile in EGPA patients, with key pathways and candidate biomarkers identified. The metabolites with high diagnostic efficacy (AUC > 0.8) might serve as candidate diagnostic biomarkers for EGPA and its differentiation from BA. These observations provided novel insights into the metabolic basis of EGPA pathogenesis and might provide valuable references for the clinical management of this rare disease.

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Cite This Study

Su et al. (2026) studied this question.

synapsesocial.com/papers/6a05680ea550a87e60a2068ahttps://doi.org/10.1371/journal.pone.0343182
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