Chromatin interactions reveal novel gene targets for drug repositioning in rheumatic diseases. Issue 8 (15th August 2019)

• Record Type: Journal Article
• Authors: Martin, Paul; Ding, James; Duffus, Kate; Gaddi, Vasanthi Priyadarshini; McGovern, Amanda; Ray-Jones, Helen; Yarwood, Annie; Worthington, Jane; Barton, Anne; Orozco, Gisela
• Is Part Of: Annals of the rheumatic diseases. Volume 78:Issue 8(2019)
• Page Start: 1127
• Publication Date: 2019-08-15
• Subjects: rheumatic diseases -- GWAS -- functional genomics -- drug repositioning; Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2018-214649
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : 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.