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(MRC DTP) Prediction of non-response to anti-TNF therapy using demographic, clinical, drug levels and pharmacogenetics


Project Description

Background: Psoriatic arthritis (PsA) is an inflammatory arthritis, associated with the chronic skin condition psoriasis, which causes joint inflammation and erosion of joints leading to disability. PsA is estimated to affect up to 1% of the population and affects up to 30% of those with psoriasis. The disease causes painful, stiff and swollen joints. It is a genetically complex disease, characterised by environmental and genetic risk factors. Biological drugs, such as anti-TNF drugs that target the Tumour Necrosis Factor (TNF) cytokine are prescribed to treat the disease. Not everyone responds to anti-TNF medication however, up to 30-40% of patients will experience non-response. Response is likely to be due to a number of different factors including demographic, clinical, drug levels and pharmacogenetics. Targeting anti-TNF medication to those who are most likely to respond would be a major shift in treatment leading to a stratified/precision medicine approach.

The aim of this project is to identify pre-treatment predictors (genetic, environmental and clinical) of non-response to anti-TNF medication in PsA and combine these into a prediction algorithm.

Methods: Patient data and blood samples will be available from the Outcomes of Treatment in PsA Study Syndicate (OUTPASS). OUTPASS is a multi-centre national UK prospective observational study established in 2013 designed to discover predictors of response to biologic treatment. The successful candidate will conduct a literature review to establish previously identified predictors of response to anti-TNF. Genotyping of genetic variants associated with response and measurement of anti-TNF drug levels will be performed. The candidate has the option of being involved in the laboratory work to develop their skillset.

This studentship will apply state-of-the-art statistical techniques, including machine learning, to produce a model of predictors of non-response. The ability of the final model to discriminate between responders and non-responders will be assessed.

Identifying biomarkers of treatment response to anti-TNF medication in PsA will enhance patient stratification and targeted therapy.

Host Environment: The University of Manchester’s research has real-world impact beyond academia. We are at the forefront of the search for solutions to some of the world’s most pressing problems. The Centre for Musculoskeletal Research has access to expert advice from statisticians, bioinformatics analysts, database experts and a number of academic rheumatologists. Professor Barton is an Academic Rheumatologist who leads a research programme identifying predictors of treatment response in inflammatory arthritis. She co-leads the MRC-Arthritis Research UK jointly funded stratified medicine programme in rheumatoid arthritis aimed at identifying genetic and genomic signatures predictive of response to biologic therapies.

http://research.bmh.manchester.ac.uk/Musculoskeletal/
https://www.research.manchester.ac.uk/portal/anne.barton.html
https://www.research.manchester.ac.uk/portal/james.bluett.html

Entry Requirements:
Applications are invited from UK/EU nationals only. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.

Funding Notes

This project is to be funded under the MRC Doctoral Training Partnership. If you are interested in this project, please make direct contact with the Principal Supervisor to arrange to discuss the project further as soon as possible. You MUST also submit an online application form - full details on how to apply can be found on the MRC DTP website View Website

As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

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