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Data from: Multi-omics analyses on rheumatoid arthritis in CD4+ T cells


‍Ha, Eunji et al. (2021), Data from: Multi-omics analyses on rheumatoid arthritis in CD4+ T cells, Dryad, Dataset,


Objective: CD4+ T cells have been suggested as the most disease-relevant cell type in rheumatoid arthritis (RA) in which RA-risk non-coding variants exhibit allele-specific effects on regulation of RA-driving genes. This study aimed to understand RA-specific signatures in CD4+ T cells using multi-omics data, interpreting inter-omics relationships in shaping the RA transcriptomic landscape.

Methods: We profiled genome-wide variants, gene expression, and DNA methylation in CD4+ T cells from 82 RA patients and 40 healthy controls using high-throughput technologies. We investigated differentially expressed genes (DEGs) and differentially methylated regions (DMRs) in RA and localized quantitative trait loci (QTLs) for expression and methylation. We then integrated these based on individual-level correlations to inspect DEG-regulating sources and investigated the potential regulatory roles of RA-risk variants by a partitioned-heritability enrichment analysis with RA genome-wide association summary statistics.

Results: A large number of RA-specific DEGs were identified (n=2,575), highlighting T-cell differentiation and activation pathways. RA-specific DMRs, preferentially located in T-cell regulatory regions, were correlated with the expression levels of 548 DEGs mostly in the same topologically associating domains. In addition, expressional variances in 771 and 83 DEGs were partially explained by expression QTLs for DEGs and methylation QTLs for DEG-correlated DMRs, respectively. A large number of RA variants were moderately to strongly correlated with meQTLs. DEG-correlated DMRs, enriched with meQTLs, had strongly enriched heritability of RA.

Conclusion: Our findings revealed that the methylomic changes, driven by RA heritability-explaining variants, shape the differential expression of a substantial fraction of DEGs in CD4+ T cells in RA patients, reinforcing the importance of a multi-dimensional approach in disease-relevant tissues.


The different genetic patterns (differentially expressed genes and methylated regions) between RA patients and healthy controls were identified from microarray and NGS data analyses in a Korean cohort (n=122). In addition, eQTLs and meQTLs were detected by linear regression.

Usage Notes

Please find detailed information from our research article:

Eunji Ha and So-Young Bang et al.; "Genetic variants shape rheumatoid arthritis-specific transcriptomic features in CD4+ T cells through differential DNA methylation, explaining a substantial proportion of heritability."; Annals of the Rheumatic Disease; in press.


Ministry of Science, ICT and Future Planning, Award: 2017R1E1A1A01076388

Korea NIH, Award: 2012-N73006-01;2017-NI73002-02

Korea Disease Control and Prevention Agency, Award: 4848-308;4845-301

Hanyang University Institute for Rheumatology Research

Korea NIH, Award: 2012-N73006-01;2017-NI73002-02

Hanyang University Institute for Rheumatology Research