Epigenetic reprogramming of tissue-resident memory T cells in chronic inflammatory disorde

124 patients with rheumatoid arthritis, inflammatory bowel disease, or psoriasis and 35 healthy controls contributed samples for this integrative multi-omics atlas. The dataset includes results from scATAC-seq, ChIP-seq, whole-genome bisulfite sequencing, and scRNA-seq, identifying 847 differentially methylated regions and 1,239 altered chromatin accessibility peaks. Chen Ling published the dataset on figshare in 2026, revealing tissue-specific epigenetic vulnerabilities and potential therapeutic targets like DNMT1 and EZH2.

Use Cases

• Train machine learning classifiers to distinguish pathogenic from protective T cell states based on the described multi-omics features.
• Analyze tissue-specific epigenetic defects, such as FOXP3 hypermethylation in intestinal TRM cells or elevated H3K27me3 in synovial TRM cells.
• Investigate the role of TET2-mediated demethylation at pro-inflammatory enhancers for cytokines like IL-17A and TNF.
• Validate potential drug targets (e.g., DNMT1, EZH2) by modeling their inhibition effects on epigenetic reprogramming.

Strengths

• Includes multi-omics data from 159 total samples (124 patients, 35 controls) across three distinct chronic inflammatory diseases.
• Reports specific, quantified epigenetic changes, including 847 differentially methylated regions and methylation percentage changes (e.g., -87.3% for TNF).
• Cell samples had high purity (>92%) and viability (>94%), and a machine learning model achieved 94.2% accuracy for cell classification.

Limitations

• The primary data files are listed as JPG format (1020.8 KB), which suggests the dataset may contain summary figures or plots rather than the raw multi-omics data tables.
• Row count and column-level documentation are unknown, limiting assessment of the dataset's structure and granularity.
• The authors note limitations include an ex vivo validation system and the need for larger multicentric studies to validate biomarkers.

Provenance

Source

figshare, author Chen Ling.

Collection Method

Integrative multi-omics analysis (scATAC-seq, ChIP-seq, whole-genome bisulfite sequencing, scRNA-seq) of purified TRM cells from patient and control samples.

Freshness

Last updated 2026-06-03 11:02:20.