02761nas a2200373   4500000000100000008004100001260002100042653002600063653001700089653004800106653001100154653002300165653001800188653003800206653001200244100001500256700001700271700001500288700001300303700001700316700002500333700001600358700001400374700001500388700001500403700002100418700001600439245020300455856006800658300001100726490000700737520162900744022001402373       2026                            d  c07/2026bMDPI AG10aMycobacterium leprae 10aMetabolomics10a liquid chromatography–mass spectrometry 10aBiopsy10aParaffin Embedding10areal-time PCR10aEnzyme-Linked Immunosorbent Assay10aleprosy1 aPereira NV1 aDornelas BDC1 aCosta WVTD1 aZana JPS1 aAraújo ENDS1 aRodrigues Campos FDA1 aCampos DRDO1 aSilva TDC1 aSouza HOAD1 aMartins MM1 aGoulart Filho LR1 aGoulart IMB00aMass Spectrometry-Based Metabolomics in Formalin-Fixed Paraffin-Embedded Skin Biopsies Identifies Potential Candidate Biomarkers for Leprosy Progression Across the Ridley–Jopling Clinical Spectrum  uhttps://www.mdpi.com/2076-2607/14/7/1567/pdf?version=1784286197  a1 - 210 v143 a<jats:p>Leprosy presents a broad clinical–immunological spectrum, whose heterogeneity challenges early diagnosis and disease stratification. Metabolomic approaches have emerged as promising tools for identifying potential biomarkers associated with the disease’s pathophysiology. This study aimed to investigate metabolic profiles associated with the different clinical forms of leprosy using untargeted metabolomics in formalin-fixed paraffin-embedded (FFPE) tissue samples. A retrospective cross-sectional study was conducted with 55 patients classified according to the Ridley–Jopling spectrum. Metabolites were extracted from FFPE skin biopsies and analyzed by liquid chromatography–mass spectrometry (LC-MS). From 908 metabolites initially detected, 27 were retained after frequency filtering. Six metabolites ultimately met the criteria of one-way analysis of variance (ANOVA, p &lt; 0.05) and fold-change (FC ≥ 2.0) for differential expression, while N-stearoyl tryptophan was identified as an additional candidate metabolite based on its contribution to multivariate group discrimination. These included 11-hydroperoxy-H4-neuroprostane, which showed a specific association with bacterial load, and the Gly-Pro-Lys tripeptide, which correlated with markers of infection progression. Metabolomics applied to FFPE samples proved feasible for discriminating the clinical spectrum of leprosy and annotating signatures associated with immune response. This approach represents an innovative strategy for exploratory biomarker discovery using archived histopathological samples in translational research.</jats:p>  a2076-2607