Prof A Barton, Dr D Plant, Dr H Guo
Applications accepted all year round
Self-Funded PhD Students Only
About the Project
Rheumatoid arthritis (RA) has a heterogeneous patient population with multiple disease courses. However, standardised treatment means that individual patients may not be on treatment targeted to their needs. To date no reliable biomarkers of treatment response have been identified. Recent technological advances have expanded the breadth of omics data, for example transcriptomics, methylomics and metabolomics which may be investigated in order to identify reliable biomarkers. A number of research groups, including ours, are working toward this aim and it is becoming increasingly clear that an integrative, systems biology approach to analysis of molecular data will be needed if we are to succeed.
We have collected a prospective longitudinal cohort (n > 2,000 subjects) called the ‘Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate (BRAGGSS)’, which contains clinical data from patients about to start treatment with biologic drugs and at 3, 6 and 12 months post-treatment. DNA variation (n > 1,500), Transcriptomics (n > 200), DNA methylation (n > 100) and metabolomics (n > 80) data are already amassed within BRAGGSS and data generation is ongoing.
Multi-stage and meta-dimensional analysis methods will be developed to model the relationships between molecular data and changes in disease activity across follow-up time-points. The challenge will be to integrating data measured on different scales and modelling time-varying clinical data collected longitudinally.
Potential outcomes/impact: This studentship will bring together the disciplines of RA epidemiology, computer science, statistics and genetics / genomics to improve understanding of the mechanisms underpinning inter-individual differences in on-treatment disease activity and therapeutic response. The outcome of this work will be disseminated to academic beneficiaries via peer reviewed publication and presentations at national and international conferences and could directly influence current clinical practice and inform the development of new interventions to improve treatment pathways for individuals with RA.
Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a health, biomedical sciences or biostatistics subject.
Funding Notes
This project has a Standard Band fee. Details of our different fee bands can be found on our website (https://www.bmh.manchester.ac.uk/study/research/fees/). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (https://www.bmh.manchester.ac.uk/study/research/apply/).
Informal enquiries may be made directly to the primary supervisor.
References
1. Oliver J, Plant D, Webster AP, Barton A. Genetic and genomic markers of anti-TNF treatment response in rheumatoid arthritis. Biomark Med 2015; 9(6): 499-512.
2. Plant, D., Webster, A., Nair, N., Oliver, J., Smith, S. L., Eyre, S., Hyrich, K. L., Wilson, A. G., Morgan, A. W., Isaacs, J., Worthington, J. & Barton, A. Differential methylation as a biomarker of response to etanercept in patients with rheumatoid arthritis. Arthritis & Rheumatism. 68, 6, p. 1353–1360.
3. Guo H, Fortune MD, Burren OS, Schofield E, Todd JA & Wallace C. Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases. Human Molecular Genetics 2015; 24(12): 3305-3313.
4. Ferreira RC, Guo H, Coulson RMR, Smyth DJ, Pekalski ML & others. A type I Interferon transcriptional signature precedes autoimmunity in children genetically at risk for type 1 diabetes. Diabetes 2014; 63(7): 2538-2550.
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