Up to 90% of people with immune mediated inflammatory disorders (IMID) experience severe, sometimes debilitating, fatigue. Fatigue is the experience of intense tiredness or exhaustion often unrelated to energy exertion and not relieved by rest. The causes of this fatigue are not known, although there is suggestive evidence that inflammation plays an important role.
The aim of this PhD is to identify the inflammatory mechanisms of fatigue in patients with immune mediated inflammatory disease (IMID) including rheumatoid arthritis and psoriasis. The PhD project will use data from the NIHR IMID-Bioresource, a data-rich resource of patients diagnosed with an IMID. The PhD project will be composed of three workstreams:
Workstream 1 – Descriptive epidemiology (months 0-12).
Descriptive epidemiology techniques will describe the prevalence of fatigue in patients stratified by important characteristics including age, sex, socioeconomic status, and comorbidity status. Bayesian analysis techniques will standardise prevalence estimates to the UK population of patients. Findings will be compared between those with different primary disease diagnoses.
Workstream 2 – Genetic association analysis (months 12-24).
Previously identified and novel genes associated with inflammatory pathways will be identified. Using a candidate gene approach, these will be tested for association with fatigue. Results will be validated in an independent replication cohort.
Workstream 3 – Causal inference analysis (months 24-36).
The genes identified in workstream 2 will be included in Directed Acyclic Graph(s) (DAG) along with other known and hypothesised mechanisms. Using causal inference methods to explore direct and indirect causal pathways, the relative strengths of these mechanisms will be tested. The potential efficacy of interventions targeting those mechanisms will be explored.
The results will inform future work to develop and/or repurpose existing interventions for this key patient priority.
Applicants are expected to hold, or about to obtain, a minimum 2:1 undergraduate degree (or equivalent) in epidemiology, statistics, data science, or another related field. A Master’s degree in a relevant subject and/or experience in a related discipline is desirable.
This PhD would be attractive to candidates from an epidemiological, clinical, or statistical background looking to increase their knowledge and experience in applied research.
Before you Apply
Applicants must make direct contact with the primary supervisor before applying to discuss their interest in the project. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application.
How to Apply
To be considered for this project you MUST submit a formal online application form - full details on how to apply can be found on the BRC website https://www.bmh.manchester.ac.uk/study/research/funded-programmes/manchester-brc-phd-studentships/
Your application form must be accompanied by a number of supporting documents by the advertised deadlines. Without all the required documents submitted at the time of application, your application will not be processed and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered. If you have any queries regarding making an application please contact our admissions team.
Equality, Diversity and Inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/