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Genetic variants shape rheumatoid arthritis-specific transcriptomic features in CD4+ T cells through differential DNA methylation, explaining a substantial proportion of heritability
  1. Eunji Ha1,
  2. So-Young Bang2,3,
  3. Jiwoo Lim1,
  4. Jun Ho Yun4,
  5. Jeong-Min Kim4,
  6. Jae-Bum Bae4,
  7. Hye-Soon Lee2,3,
  8. Bong-Jo Kim4,
  9. Kwangwoo Kim1,
  10. Sang-Cheol Bae2,3
  1. 1Department of Biology and Department of Life and Nanopharmaceutical SciencesBiology, Kyung Hee University, Seoul, Republic of Korea
  2. 2Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Republic of Korea
  3. 3Hanyang University Institute for Rheumatology Research, Seoul, Republic of Korea
  4. 4Division of Genome Science, Department of Precision Medicine, National Institute of Health, Osong Health Technology Administration Complex, Cheongju, Republic of Korea
  1. Correspondence to Professor Sang-Cheol Bae, Department of Rheumatology, Hanyang University Hospital for Rheumatic Diseases, Seoul, Republic of Korea; scbae{at}; Professor Kwangwoo Kim, Department of Biology, Kyung Hee University, Seoul, Republic of Korea; kkim{at}; Dr Bong-Jo Kim, Division of Genome Science, Department of Precision Medicine, National Institute of Health, Chungcheongbuk-do, Republic of Korea; kbj6181{at}


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.

  • arthritis
  • rheumatoid
  • polymorphism
  • genetic
  • 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

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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