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OP0298 Chromatin interactions reveal novel gene targets for drug repositioning in rheumatic diseases
  1. P Martin1,
  2. K Duffus1,
  3. A McGovern1,
  4. A Yarwood1,
  5. A Barton1,2,
  6. J Worthington1,2,
  7. S Eyre1,
  8. G Orozco1
  1. 1Arthritis Research UK Centre for Genetics and Genomics, University of Manchester
  2. 2NIHR Manchester Musculoskeletal Biomedical Research Unit, Central Manchester Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom


Background The treatment of rheumatic diseases can be both expensive and ineffective with up to 1/3 of patient's failing to respond to current treatments. There is therefore a need to identify new treatments and to target these to individual patients. Although genetic studies have been successful in identifying common variation associated with disease susceptibility, a large proportion of these lie outside protein-coding regions. Many show enhancer activity but it is often unclear which gene(s) they regulate and how they contribute to disease. Chromatin folding brings linearly distant areas of the genome, such as promoters and enhancers, into close proximity, driving gene expression. Capture Hi-C (CHi-C) interrogates these interactions in a high-throughput, high-resolution manner, linking implicated enhancers to causal genes.

Objectives Utilising our existing CHi-C data on 3 rheumatic diseases, RA, JIA and PsA, targeting all known genetic associations, we explored the potential to identify candidate causal genes that are targets for existing drugs, which could be repositioned for use in these diseases.

Methods Chromatin interaction data for T- and B-cells in the 3 diseases was analysed using CHiCAGO v2 using a score cut-off of ≥5. Interactions between disease regions and promoters were identified using BEDTOOLS v2.21.0 and intersected with drug targets from DrugBank v4.5.0. Existing treatments for each disease were identified by the presence of the relevant name in the “indication” field.

Results Overall 850 genes were identified as interacting with a disease associated region. Of these, 61 are existing drug targets (303 drugs) (Table 1) and 9 are existing therapies used in the treatment of disease, primarily RA.

Table 1.

Summary of drug targets identified by CHi-C

Conclusions Our study identifies genes which are implicated in disease, are the target of existing drugs and offer the potential for drug repositioning. Of the potential drugs identified for RA, 14 are used in the treatment of various cancers and 11 are used in the treatment of diabetes and multiple sclerosis. Interestingly, 17 potential drugs identified for PsA are used in the treatment of schizophrenia and 11 in the treatment of hypertension. This data shows a novel insight into how functional annotation of genetic associations in rheumatic diseases can provide gene targets for re-positioned therapies.

Acknowledgements This work was funded by Wellcome Trust Research Career Development Fellowship (095684); Arthritis Research UK (grant numbers 20385, 20571); Wellcome Trust (097820/Z/11/B); European Union's FP7 Health Programme (FP7-HEALTH-F2–2012–305549, Euro-TEAM, FP7/2007–2013); Innovative Medicines Initiative (BeTheCure project 115142); Medical Research Council (MR/K015346/1); National Institute for Health Research Manchester Musculoskeletal Biomedical Research Unit; Biotechnology and Biological Sciences Research Council UK (BBS/E/B/000C0405).

Disclosure of Interest None declared

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