Full Papers
Targeting the MICA-mediated oxidative stress-immune axis: a novel therapeutic strategy for ankylosing spondylitis
R. He1, Z. Huang2, X. Qin3, J. Xue4, J. Chen5, B. Qin6, D. Liu7, S. Wu8, T. Kang9, X. Zhan10, C. Liu11
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. zhanxinli@stu.gxmu.edu.cn
- The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. liuchong@stu.gxmu.edu.cn
CER19369
Full Papers
Received: 28/09/2025
Accepted : 30/01/2026
In Press: 18/03/2026
Abstract
OBJECTIVES:
Ankylosing spondylitis (AS) involves a complex interplay between oxidative stress (OS) and immune dysregulation, yet the precise molecular links involved remain unclear.
METHODS:
OS-related genes were obtained from the GeneCards database. Differential expression analysis was performed on mRNA microarray (MA) data to identify OS-associated differentially expressed genes (DEGs). A two-sample Mendelian randomisation analysis was conducted to assess the causal relationships between OS-related genes and AS risk at the protein level. Immune cell mediation was further examined using genetic information from 731 immune phenotypes. Additionally, Logistic regression was used to examine the association between immune cell profiles and AS risk. The findings were further validated via experimental study using western blotting (WB) and single-cell RNA-seq (scRNA-seq) data.
RESULTS:
We found that the MICA protein is a key AS risk modulator via integrative omics analyses, with protein abundance showing a positive association (OR=1.89; PFDR=3.6×10–4). Mediation analyses revealed that the genetic effects of these genes were partially transmitted through specific T cell subsets, particularly CD28+ resting Tregs. The mediated proportion was 82.3%. Clinical validations confirmed lymphocyte-associated protection (OR: 0.64, 95%CI: 0.54–0.76). scRNA-seq analyses demonstrated significant MICA upregulation in AS-drived T cells, confirmed by Western blot analysis.
CONCLUSIONS:
This integrative multiomics analysis revealed OS-related genes as causal drivers of AS through immune dysregulation pathways. Targeting OS-related immune mechanisms may offer novel precision therapeutic strategies for AS.
