ArticleFrontiers in cellular and infection microbiology2026
Multi-omics analysis identifies macrophage immunometabolic signatures in ulcerative colitis.
Article in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by intestinal immune dysregulation and mucosal barrier dysfunction. Macrophages play central roles in gut immunity, yet their metabolic reprogramming and heterogeneity in UC remain insufficiently characterized. Methods: We integrated single-cell RNA sequencing (scRNA-seq), bulk transcriptomics, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (LASSO, SVM-RFE, and Random Forest) to identify candidate macrophage-associated metabolic regulators in UC. Pseudotime trajectory, CellChat, and functional enrichment analyses were used to assess differentiation, intercellular interactions, and pathway involvement. Diagnostic performance was evaluated using ROC curves and validated in independent datasets. Experimental validation was performed using Hematoxylin and Eosin (H&E) staining for histopathological assessment and Western blotting for protein expression analysis. Results: scRNA-seq identified 505 macrophage-specific genes, with pseudotime analysis suggesting differentiation branches marked by RGCC and FOSL2. Transcriptomic profiling revealed 1,058 differentially expressed genes, enriched in TNF, epithelial-mesenchymal transition, and NF-κB pathways. Six macrophage-associated immunometabolic genes (CYBB, CR1, INPP5D, CTSH, IFI16, and NCF4) were identified through WGCNA and machine learning analyses. These genes were strongly correlated with macrophage infiltration and cytokine signaling, showing high diagnostic performance (AUC > 0.98), although potential overfitting cannot be fully excluded. Consensus clustering stratified UC patients into two molecular subtypes, with Cluster 1 exhibiting a proinflammatory phenotype. H&E staining confirmed characteristic mucosal inflammation and epithelial damage in UC tissues, while Western blotting validated the upregulation of the six key regulators in UC tissues. Conclusion: This multi-omics analysis identifies six macrophage metabolic regulators (CYBB, CR1, INPP5D, CTSH, IFI16, and NCF4) with potential diagnostic relevance in UC. Experimental validation provides supportive evidence for their association with macrophage-related immunometabolic alterations in UC.
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