Epigenetic reprogramming of tissue-resident memory T cells in chronic inflammatory disorders and implications for targeted therapies.

IF 3.1 4区 医学 Q2 GENETICS & HEREDITY
Epigenomics Pub Date : 2026-06-01 Epub Date: 2026-06-03 DOI:10.1080/17501911.2026.2678920
Chen Ling, Haytham F Isleem, Ghanshyam G Tejani
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引用次数: 0

Abstract

Background: Tissue-resident memory T (TRM) cells play a role in causing long-term tissue injury in chronic inflammatory diseases via pathological epigenetic reprogramming. Nevertheless, the epigenetic processes that cause this malfunction have not been well defined.

Research design and methods: We performed integrative multi-omics analysis of TRM cells (CD3+CD8+CD69+CD103+, >92% purity, >94% viability) from 124 patients (41 rheumatoid arthritis, 43 inflammatory bowel disease, 40 psoriasis) and 35 healthy controls, employing scATAC-seq, ChIP-seq, whole-genome bisulfite sequencing, and scRNA-seq.

Results: We identified 847 differentially methylated regions (p<0.001) and 1,239 altered chromatin accessibility peaks. Pathogenic programming was sustained through TET2-mediated demethylation of pro-inflammatory enhancers for IL-17A (-43.2% methylation) and TNF (-87.3% methylation). Tissue-specific defects included FOXP3 hypermethylation (+47.3%) in intestinal TRM and elevated H3K27me3 deposition (2.3-fold) in synovial TRM. Combined inhibition using the DNMT1-targeting degrader GSK-3484862 and the EZH2 inhibitor GSK126 reversed pathological programming, reducing cytokine production by >80% in ex vivo assays. Machine learning classification achieved 94.2% accuracy (95% CI: 91.3-97.1%) distinguishing pathogenic from protective TRM cells.

Conclusions: This first epigenetic atlas of TRM cells in chronic inflammation reveals tissue-specific vulnerabilities, therapeutic targets (DNMT1, EZH2), and patient stratification biomarkers. Limitations include the ex vivo validation system and the need for larger multicentric biomarker validation studies.

慢性炎症性疾病中组织驻留记忆T细胞的表观遗传重编程及其靶向治疗的意义。
背景:组织驻留记忆T (TRM)细胞通过病理表观遗传重编程在慢性炎症性疾病中引起长期组织损伤中发挥作用。然而,导致这种功能障碍的表观遗传过程尚未得到很好的定义。研究设计和方法:采用scATAC-seq、ChIP-seq、全基因组亚硫酸盐测序和scRNA-seq,对124例患者(41例类风湿性关节炎、43例炎症性肠病、40例牛皮癣)和35例健康对照的TRM细胞(CD3+CD8+CD69+CD103+, >纯度为92%,>活力为94%)进行了综合多组学分析。结果:我们在离体实验中鉴定出847个差异甲基化区域(p80%)。机器学习分类区分致病性和保护性TRM细胞的准确率达到94.2% (95% CI: 91.3-97.1%)。结论:慢性炎症中TRM细胞的首个表观遗传图谱揭示了组织特异性脆弱性、治疗靶点(DNMT1、EZH2)和患者分层生物标志物。局限性包括离体验证系统和需要更大的多中心生物标志物验证研究。
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来源期刊
Epigenomics
Epigenomics GENETICS & HEREDITY-
CiteScore
5.80
自引率
2.60%
发文量
95
审稿时长
>12 weeks
期刊介绍: Epigenomics provides the forum to address the rapidly progressing research developments in this ever-expanding field; to report on the major challenges ahead and critical advances that are propelling the science forward. The journal delivers this information in concise, at-a-glance article formats – invaluable to a time constrained community. Substantial developments in our current knowledge and understanding of genomics and epigenetics are constantly being made, yet this field is still in its infancy. Epigenomics provides a critical overview of the latest and most significant advances as they unfold and explores their potential application in the clinical setting.
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