Frontiers in Immunology (Jul 2024)

Precision therapy for ulcerative colitis: insights from mitochondrial dysfunction interacting with the immune microenvironment

  • Yi-fan Zhang,
  • Yi-fan Zhang,
  • Meng-ying Fan,
  • Qi-rui Bai,
  • Rong Zhao,
  • Shan Song,
  • Li Wu,
  • Jun-hui Lu,
  • Jun-hui Lu,
  • Jing-wei Liu,
  • Jing-wei Liu,
  • Qi Wang,
  • Yuan Li,
  • Xing Chen

DOI
https://doi.org/10.3389/fimmu.2024.1396221
Journal volume & issue
Vol. 15

Abstract

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BackgroundAccumulating evidence reveals mitochondrial dysfunction exacerbates intestinal barrier dysfunction and inflammation. Despite the growing knowledge of mitochondrial dysfunction and ulcerative colitis (UC), the mechanism of mitochondrial dysfunction in UC remains to be fully explored.MethodsWe integrated 1137 UC colon mucosal samples from 12 multicenter cohorts worldwide to create a normalized compendium. Differentially expressed mitochondria-related genes (DE-MiRGs) in individuals with UC were identified using the “Limma” R package. Unsupervised consensus clustering was utilized to determine the intrinsic subtypes of UC driven by DE-MiRGs. Weighted gene co-expression network analysis was employed to investigate module genes related to UC. Four machine learning algorithms were utilized for screening DE-MiRGs in UC and construct MiRGs diagnostic models. The models were developed utilizing the over-sampled training cohort, followed by validation in both the internal test cohort and the external validation cohort. Immune cell infiltration was assessed using the Xcell and CIBERSORT algorithms, while potential biological mechanisms were explored through GSVA and GSEA algorithms. Hub genes were selected using the PPI network.ResultsThe study identified 108 DE-MiRGs in the colonic mucosa of patients with UC compared to healthy controls, showing significant enrichment in pathways associated with mitochondrial metabolism and inflammation. The MiRGs diagnostic models for UC were constructed based on 17 signature genes identified through various machine learning algorithms, demonstrated excellent predictive capabilities. Utilizing the identified DE-MiRGs from the normalized compendium, 941 patients with UC were stratified into three subtypes characterized by distinct cellular and molecular profiles. Specifically, the metabolic subtype demonstrated enrichment in epithelial cells, the immune-inflamed subtype displayed high enrichment in antigen-presenting cells and pathways related to pro-inflammatory activation, and the transitional subtype exhibited moderate activation across all signaling pathways. Importantly, the immune-inflamed subtype exhibited a stronger correlation with superior response to four biologics: infliximab, ustekinumab, vedolizumab, and golimumab compared to the metabolic subtype.ConclusionThis analysis unveils the interplay between mitochondrial dysfunction and the immune microenvironment in UC, thereby offering novel perspectives on the potential pathogenesis of UC and precision treatment of UC patients, and identifying new therapeutic targets.

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