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Skin Biopsy for Diagnosing Discoid Lupus Erythematosus
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Mass Spectrometry-Based Metabolomics in Formalin-Fixed Paraffin-Embedded Skin Biopsies Identifies Potential Candidate
Noriel Viana Pereira1, Bruno de Carvalho Dornelas2, Willian Vargas Tenório da Costa3
1Graduate Program in Health Sciences, School of Medicine, Federal University of Uberlândia, Uberlândia 38400-902, MG, Brazil.
Microorganisms
|July 28, 2026
Summary
Metabolomics analysis of leprosy tissue samples identified distinct metabolic profiles for different disease forms. This approach aids in discovering biomarkers for leprosy diagnosis and understanding disease progression.
Area of Science:
- Biochemistry
- Immunology
- Pathophysiology
Background:
- Leprosy exhibits diverse clinical and immunological presentations, complicating diagnosis and stratification.
- Metabolomics offers potential for identifying biomarkers linked to leprosy's underlying mechanisms.
Purpose of the Study:
- To explore metabolic profiles associated with various leprosy clinical forms.
- To utilize untargeted metabolomics on formalin-fixed paraffin-embedded (FFPE) tissues for biomarker discovery.
Main Methods:
- Retrospective cross-sectional study of 55 leprosy patients classified by the Ridley-Jopling spectrum.
- Untargeted liquid chromatography-mass spectrometry (LC-MS) analysis of FFPE skin biopsies.
- Statistical analysis including ANOVA and fold-change to identify differentially expressed metabolites.
Main Results:
- Six differentially expressed metabolites were identified (ANOVA, p < 0.05; FC ≥ 2.0).
- N-stearoyl tryptophan showed discriminatory potential.
- 11-hydroperoxy-H4-neuroprostane correlated with bacterial load; Gly-Pro-Lys tripeptide correlated with infection progression markers.
Conclusions:
- Metabolomics on FFPE samples is feasible for differentiating leprosy clinical forms.
- Identified metabolic signatures are associated with immune response and disease progression.
- This method provides an innovative strategy for biomarker discovery in translational research using archived samples.
