Kennedy Trust Prize Studentships
Multi-omic analysis of patient responsiveness to TNFα inhibition in rheumatoid arthritis
Rheumatoid arthritis (RA) is a chronic inflammatory disease that affects approximately 1% of the world's population and remains a major cause of disability and premature death. The development of TNFα inhibitors has been an important step forward in the treatment of the disease but these drugs are not effective in all patients. Our group has been investigating mechanisms underlying responsiveness to anti-TNFα and we made the surprising discovery that therapeutic blockade of TNFα leads promotes IL-12/IL-23 p40 expression by monocytes and leads to an increase in the number of Th17 cells [1, 2]. In order to identify the mechanisms involved, we are using a state-of-the art proteomics technique to simultaeously quantify the expression of thousands of proteins in plasma samples from RA patients before and 12 weeks after the start of anti-TNFα therapy. In this project, the student will apply bioinformatics techniques such as network and pathway analysis to gain insight into the underlying biology of the patient responses from the differentially expressed proteins. In addition, matched samples of peripheral blood mononuclear cells will be probed using genomic and transcriptomic approaches, including RNA sequencing and SNP analysis. This will allow the identification of expression quantitative trait loci (eQTLs), hence enabling us to map the genetic factors that underpin individual differences in responsieness to TNFα inhibitors in rheumatoid arthritis.
The Kennedy Institute is a world-renowned research centre and is housed in a brand new state-of-the-art research facility. Training will be provided across the range of cell and molecular biology (Williams group), computational genomics (Sansom group) and statistical genetics (Jostins group) techniques on which the project will depend. A core curriculum of 20 lectures will be taken in the first term of year 1 to provide a solid foundation in musculoskeletal sciences, immunology and data analysis. Students will attend weekly departmental meetings and will be expected to attend seminars within the department and those relevant in the wider University. Subject-specific training will be received through our group's weekly supervision meetings. Students will also attend external scientific conferences where they will be expected to present the research findings.
- Notley CA, Inglis JJ, Alzabin S, McCann FE, McNamee KE, Williams RO: Blockade of tumor necrosis factor in collagen-induced arthritis reveals a novel immunoregulatory pathway for Th1 and Th17 cells. J Exp Med 2008, 205(11):2491-2497. 2.2
- Alzabin S, Abraham SM, Taher TE, Palfreeman A, Hull D, McNamee KE, Jawad A, Pathan E, Kinderlerer A, Taylor PC, Williams RO Mageed RA: Incomplete response of inflammatory arthritis to TNFα blockade is associated with the Th17 pathway. Ann Rheum Dis 2012, 71:1741-1748.
Bioinformatics; statistics and computational biology; immunology; musculoskeletal science; translational medicine and medical technology.
Professor Richard Williams, Kennedy Institute, University of Oxford