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Chromatin interactions reveal novel gene targets for drug repositioning in rheumatic diseases
  1. Paul Martin1,2,
  2. James Ding2,
  3. Kate Duffus2,
  4. Vasanthi Priyadarshini Gaddi2,
  5. Amanda McGovern2,
  6. Helen Ray-Jones2,3,
  7. Annie Yarwood2,3,
  8. Jane Worthington2,
  9. Anne Barton2,3,
  10. Gisela Orozco2
  1. 1 Lydia Becker Institute of Immunology and Inflammation, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
  2. 2 Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK
  3. 3 Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Centre, Manchester, UK
  1. Correspondence to Dr Gisela Orozco, Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester M13 9PT, UK; gisela.orozco{at}


Objectives There is a need to identify effective treatments for rheumatic diseases, and while genetic studies have been successful it is unclear which genes contribute to the disease. Using our existing Capture Hi-C data on three rheumatic diseases, we can identify potential causal genes which are targets for existing drugs and could be repositioned for use in rheumatic diseases.

Methods High confidence candidate causal genes were identified using Capture Hi-C data from B cells and T cells. These genes were used to interrogate drug target information from DrugBank to identify existing treatments, which could be repositioned to treat these diseases. The approach was refined using Ingenuity Pathway Analysis to identify enriched pathways and therefore further treatments relevant to the disease.

Results Overall, 454 high confidence genes were identified. Of these, 48 were drug targets (108 drugs) and 11 were existing therapies used in the treatment of rheumatic diseases. After pathway analysis refinement, 50 genes remained, 13 of which were drug targets (33 drugs). However considering targets across all enriched pathways, a further 367 drugs were identified for potential repositioning.

Conclusion Capture Hi-C has the potential to identify therapies which could be repositioned to treat rheumatic diseases. This was particularly successful for rheumatoid arthritis, where six effective, biologic treatments were identified. This approach may therefore yield new ways to treat patients, enhancing their quality of life and reducing the economic impact on healthcare providers. As additional cell types and other epigenomic data sets are generated, this prospect will improve further.

  • rheumatic diseases
  • GWAS
  • functional genomics
  • drug repositioning

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  • Handling editor Josef S Smolen

  • Contributors All authors contributed to the preparation of the manuscript. PM and GO contributed to the conception and design of the experiment. PM, JD, KD, VPG, AM, HR-J and AY contributed to the acquisition and analysis of the data. PM, JW, AB and GO contributed to the interpretation of the results.

  • Funding This work was funded by the Wellcome Trust (Senior Research Fellowship ref 207491/Z/17/Z), Versus Arthritis (grant refs 21348 and 21754 and fellowship ref 21745) and NIHR Manchester BRC.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information.

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