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Updated: Apr 13, 2026

An Adoptive Transfer Model of Rheumatoid Arthritis in Mice
Published on: June 6, 2025
Epigenetic alterations in WDFY4 DNA methylation are linked to immunoinflammatory processes in rheumatoid arthritis:
Zhen Liu1, Fan Yang1, Zhenglun Pan2
1Department of Rheumatology and Immunology, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, 266000, China.
Objective:
This study examines the relationship between WDFY4 gene DNA methylation and clinical characteristics of rheumatoid arthritis (RA) through peripheral blood analysis.
Methods:
Peripheral blood samples from 150 RA patients and 150 healthy controls were analyzed via targeted methylation sequencing. Generalized linear regression assessed associations between WDFY4 methylation haplotypes, CpG sites, and clinical markers, with adjustment for potential confounders.
Results:
RA patients exhibited significantly reduced overall WDFY4 methylation levels compared to controls (0.865 ± 0.053 vs. 0.882 ± 0.043) (FDR P = 0.0088), with six specific CpG sites showing marked hypomethylation (FDR P < 0.05). Among the 22 identified haplotypes, five differed significantly between groups. Negative correlations were observed between WDFY4 methylation and anti-CCP antibodies (ACPA), rheumatoid factor (RF), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP).
Conclusions:
WDFY4 methylation may critically influence RA pathogenesis and immunoinflammatory responses. Integrating WDFY4 methylation data with environmental factors, inflammatory markers (CRP/ESR), and autoantibodies (ACPA/RF) could enhance the understanding of RA pathophysiology and potentially aid in subgroup stratification. Key Points • Targeted methylation sequencing revealed significant WDFY4 hypomethylation at specific CpG sites in RA patients versus controls. • WDFY4 methylation levels negatively correlated with RA autoantibodies and inflammatory markers, indicating its potential role in disease mechanisms. • Integrating WDFY4 methylation with clinical data improved RA and comorbidity diagnosis, with an AUC of 0.844 for predicting pulmonary fibrosis, highlighting its novel discriminative potential.
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