Dr Stephen Sansom, Professor Paul Bowness, Dr Luke Jostins-Dean and Professor Karim Raza
Genome wide association studies (GWAS) of inflammatory arthritis have now revealed hundreds of genetic variants that are linked to different forms of inflammatory arthritis. The cell types in which these variants act to cause disease still remain, however, largely unknown. Recently, exciting breakthroughs in single-cell genomics have made it possible to build exquisitely detailed maps of cellular heterogeneity in both health and disease. In this project you will integrate information from such single-cell atlases with the results from GWAS studies in order to pin-point cells that are likely to play a causative role in inflammatory arthritis. To separate disease and non-specific inflammatory responses you will undertake a comparative analysis of rheumatoid arthritis (RA) and ankylosing spondylitis (AS), two forms of inflammatory arthritis that have different genetic associations and largely distinct clinical presentations. The project will also be informed by single-cell RNA-sequencing datasets from healthy joints which we are currently generating as part of the Human Cell Atlas project (https://www.humancellatlas.org/
One example of the genetic associations that we will be aiming to decipher is the very strong association of AS with the human leukocyte antigen (HLA) class I molecule HLA-B*27 (odds ratio=131). This observation has suggested that AS may be triggered by T-cells that recognise an ‘arthritogenic’ peptide, but such cells have not yet been found and there is also very good evidence that other cell types might be critical for disease pathogenesis1. As a second example, aside from its link with HLA-B*27, AS also has prominent genetic associations with the IL-23/IL-17 immune pathway1 but the cells through which this pathway acts in AS are also unknown. Understanding the cellular basis of AS and RA is important because current therapeutics for these conditions do not work in all patients, increase susceptibility to infection and only induce disease remission in rare cases. This research aims to provide a rational basis for the development of more effective therapeutics that target to the cellular causes, rather than symptoms, of inflammatory arthritis. The supervisory team brings together deep expertise with AS (Prof Bowness)2, RA (Prof Raza)3, statistical genetics (Dr Jostins-Dean)4 and single-cell genomics (Dr Sansom)5.
For this project you will be based at the Kennedy Institute, a world-renowned research centre, housed in a brand new, state-of-the-art facility at the University of Oxford. You will also be affiliated to the Botnar Research Centre at the University of Oxford (where Prof Bowness is located) and the Institute of Inflammation and Ageing at the University of Birmingham (where Prof Raza has his research group). As a member of the Versus Arthritis funded Research Into Inflammatory Arthritis Centre (RACE; http://www.race-gbn.org/
) you will have the opportunity to participate in and present your work at regular UK-wide RACE project meetings.
Students will become fluent in computational genomics, gain a deep understanding of statistical genetics and expert knowledge of chronic inflammatory disease. Training will be provided in data science techniques including the writing of computational pipelines with Python, the use of Linux high-performance compute clusters, and statistical data analysis and visualisation with R. Students will have the opportunity to utilise machine learning approaches and will perform integrated analyses with “big data” from sources such as the Human Cell Atlas and ImmGen projects.
For more information on our work please visit our websites: https://www.kennedy.ox.ac.uk/research/computational-genomics
(Sansom group), https://research.birmingham.ac.uk/portal/en/persons/karim-raza(57203080-c0da-41c5-ab84-a8710567bf53).html
(Raza group), https://www.kennedy.ox.ac.uk/research/jostins-group-statistical-genetics-of-immune-variation
(Jostins-Dean group), https://www.ndorms.ox.ac.uk/research-groups/immunology-of-Ankylosing-Spondylitis
A core curriculum of lectures will be taken in the first term to provide a solid foundation in a broad range of subjects including musculoskeletal biology, inflammation, epigenetics, translational immunology, data analysis and the microbiome. Students will attend regular seminars within the department and those relevant in the wider University. Students will be expected to present data regularly in the departmental PGR seminars, group meetings and to attend external conferences to present their research globally.
Students will have access to various courses run by the Medical Sciences Division Skills Training Team and other departments. All students are required to attend a 2 - day Statistical and Experimental Design course at NDORMS.
Bioinformatics, Statistics and Computational Biology; Genes, Genetics, Epigenetics and Genomics; Immunology; Musculoskeletal Science; Translational Medicine and Medical Technology
Please contact Dr Stephen Sansom ([email protected]
), Professor Paul Bowness ([email protected]
), Dr Luke Jostins-Dean ([email protected]
) or Professor Karim Raza ([email protected]
(1) Progress in our understanding of the pathogenesis of ankylosing spondylitis. Simone D, Al Mossawi and Bowness P. Rheumatology (Oxford), 2018
(2) Unique transcriptome signatures and GM-CSF expression in lymphocytes from patients with spondyloarthritis. Al-Mossawi et. al. Nature Communications, 2017
(3) New pathogenic insights into rheumatoid arthritis. Gurpreet Jutley, Karim Raza & Christopher Buckley. Current Opinion in Rheumatology, 2015
(4) Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci. David Ellinghaus, et. al. Nature Genetics, 2016
(5) Distinct fibroblast subsets drive inflammation and damage in arthritis. Adam P. Croft, et. al. Nature, 2019