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 patients with RA and 40 healthy controls using high-throughput technologies. We investigated differentially expressed genes (DEGs) and differential methylated regions (DMRs) in RA and localised 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=2575), 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 (meQTLs) 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 patients with RA, reinforcing the importance of a multidimensional approach in disease-relevant tissues.
- autoimmune diseases
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Handling editor Josef S Smolen
EH and S-YB contributed equally.
Contributors KK, SCB and BJK designed the study. SYB, HSL and SCB recruited and characterised patients with rheumatoid arthritis and controls. SYB, JHY, JMK, JBB, HSL, BJK, KK and SCB generated genetic, epigenetic and transcriptomic data. EH, JL, KK and SCB analysed the data and interpreted the results. EH, KK and SCB wrote the manuscript. All authors reviewed and approved the manuscript.
Funding This study is supported by Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Science, ICT & Future Planning (2017R1E1A1A01076388), Hanyang University Institute for Rheumatology Research and the National Institute of Health (2012-N73006-01, 2017-NI73002-02). Expression and DNA methylation data were generated as a part of Korean Epigenome Project (4848–308) with the support of the Korea Disease Control and Prevention Agency. KoreanChip was designed by Korean Genome Analysis Project (4845–301) that was supported by the Korea Disease Control and Prevention Agency.
Competing interests None declared.
Patient consent for publication Not required.
Ethics approval This study was approved by the Institutional Review Board at Hanyang University (HYG-11-008-1).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available in a public, open access repository. All data relevant to the study are included in the article or uploaded as supplementary information. The summary statistics of DEGs, DMRs, eQTLs and meQTLs in this study are available at https://doi.org/10.5061/dryad.w0vt4b8pw.
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