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Research Article: RNF213 marks a regulatory T-cell subset associated with ulcerative colitis

Date Published: 2026-07-06

Abstract:
Ulcerative colitis (UC) is a nonspecific autoimmune disease, the etiology and pathogenesis of which remain unclear. Identifying new disease targets could inform clinical diagnosis and treatment. We integrated single-cell RNA sequencing (scRNA-seq) and bulk transcriptome data from UC patients. We screened key biomarkers and constructed a nomogram diagnostic model through three machine learning algorithms (LASSO, SVM-RFE, and Boruta). In situ validation was conducted on mucosal tissue sections from clinical UC and healthy controls using multiplex immunofluorescence (mIF). To investigate the intracellular mechanisms by which RNF213 regulates Tregs, we employed scTenifoldKnk and CellChat analyses. Potential targeted compounds were predicted based on the DSigDB and HERB databases. Five UC-specific ubiquitination biomarkers were identified: ZC3H12A, ENC1, RNF213, MAP3K5, and RMND5A. Among them, RNF213 demonstrated superior diagnostic performance with an AUC greater than 0.9 in both training and validation cohorts. Single-cell localization and in situ mIF quantification indicated that RNF213 was enriched in mucosal Tregs from UC patients. RNF213 + Tregs were increased in UC compared with healthy controls. In-silico RNF213 perturbation analysis suggested that RNF213-enriched Tregs may be associated with transcriptional programs related to mitochondrial proton transport and ATP synthesis. CellChat analysis further predicted altered ligand-receptor interaction patterns among RNF213 + Tregs and other immune cell populations, including monocytes, macrophages, and B cells. This study identifies RNF213 as a biomarker enriched in UC-associated mucosal Tregs. RNF213 + Tregs may represent a transcriptionally and spatially distinct Treg subset associated with inflammatory activity in UC.

Introduction:
Ulcerative colitis (UC) is a nonspecific autoimmune disease, the etiology and pathogenesis of which remain unclear. Identifying new disease targets could inform clinical diagnosis and treatment.

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