Projects per year
Abstract
Objectives
There is a need to identify effective treatments for rheumatic diseases and whilst genetic studies have been successful, it is unclear which genes contribute to disease. Using our existing Capture Hi-C data on 3 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 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 utilising Ingenuity Pathway Analysis to identify enriched pathways and therefore, further treatments, relevant to 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 re-positioning.
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 datasets are generated, this prospect will improve further.
There is a need to identify effective treatments for rheumatic diseases and whilst genetic studies have been successful, it is unclear which genes contribute to disease. Using our existing Capture Hi-C data on 3 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 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 utilising Ingenuity Pathway Analysis to identify enriched pathways and therefore, further treatments, relevant to 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 re-positioning.
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 datasets are generated, this prospect will improve further.
Original language | English |
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Pages (from-to) | 1127-1134 |
Journal | Annals Of Rheumatic Diseases |
Volume | 78 |
DOIs | |
Publication status | Published - 15 May 2019 |
Keywords
- GWAS
- drug repositioning
- functional genomics
- rheumatic diseases
Fingerprint
Dive into the research topics of 'Chromatin interactions reveal novel gene targets for drug repositioning in rheumatic diseases'. Together they form a unique fingerprint.Projects
- 1 Finished
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Arthritis Research UK Centre of Excellence in the Genetics of Rheumatic Diseases.
Worthington, J. (PI), Barton, A. (CoI), Black, G. (CoI), Crow, Y. (CoI), Eyre, S. (CoI), Raychaudhuri, S. (CoI) & Thomson, W. (CoI)
1/08/13 → 31/07/18
Project: Research