Website The University of Manchester
Details
Most people at high genetic risk of immune-mediated inflammatory disease never develop disease, while some develop disease despite apparently low inherited risk. These “genetically discordant” individuals may reveal mechanisms of disease protection, resilience and susceptibility that are missed by conventional genetic risk prediction.
This PhD will use UK Biobank, with replication in All of Us, to study why genetic risk does or does not translate into clinical disease. The project will integrate polygenic risk, electronic health records, environmental exposures and sequencing data across rheumatoid arthritis, axial spondyloarthritis and psoriatic disease.
Study 1: Environmental modifiers of genetic risk
The student will identify individuals with high (common variant) polygenic risk who remain disease-free, and individuals with low genetic risk who develop disease. They will test whether lifestyle and other potentially modifiable factors help explain resilience or susceptibility.
Study 2: Rare variant discovery
The student will use sequencing data to identify rare coding variants, protective alleles and genetic modifiers associated with discordant disease status. This study will investigate whether genetic architecture beyond common polygenic risk helps explain why some individuals unexpectedly develop disease, while others remain protected.
Study 3: Pre-diagnostic health trajectories
The student will examine whether longitudinal health records before diagnosis reveal distinct trajectories into disease. This will include temporal patterns of comorbidity accumulation before clinical onset.
The supervisory team brings together clinical epidemiology, rheumatology, and internationally recognised leadership in immune-mediated disease genetics, providing an exceptional environment for training at the interface of genetic and traditional epidemiology.
The student will gain training in genetic epidemiology, longitudinal modelling, rare variant analysis, and biobank-scale health data science, preparing them for a career in academia, biotechnology, pharmaceutical research, precision medicine or applied health data science.
Eligibility
Candidates should hold, or be close to obtaining, a first-class or strong upper second-class honours degree, or equivalent, in a relevant quantitative, biomedical or population health discipline. Suitable backgrounds include epidemiology, biostatistics, bioinformatics, statistical genetics, data science, computational biology, public health, genetics, medicine or a related field.
We particularly encourage applications from candidates with strong quantitative aptitude, experience using statistical software such as R or Python, and an interest in applying large-scale health and genomic data to clinically important questions in immune-mediated disease. Prior experience with epidemiological analysis, regression modelling, electronic health record data, polygenic risk scores, sequencing data or longitudinal analysis would be advantageous. Candidates should be intellectually curious, methodologically rigorous, highly motivated, and keen to develop as independent researchers at the interface of epidemiology and genomics.
Before you Apply
Applicants must make direct contact with preferred supervisors before applying. 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 – on the application form select PhD Genomics Programme. Full details on how to apply can be found on the Website: How to apply for postgraduate research at The University of Manchester
If you have any queries regarding making an application please contact our admissions team FBMH.doctoralacademy.admissions@manchester.ac.uk
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: Equality, diversity and inclusion (EDI | Postgraduate Research | Biology, Medicine and Health | University of Manchester
Funding Notes
Applications are invited from self-funded students. This project has a Band 1 (low) fee. Details of our different fee bands can be found on our website https://www.bmh.manchester.ac.uk/study/research/fees/
References
Suzuki K […] Morris AP. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature. 2024
ordoff M […] Morris AP, Bowes J. Integration of genetic and clinical risk factors for risk classification of uveitis in patients with juvenile idiopathic arthritis. Arthritis & Rheumatology. 2024
Morris AP, Zeggini E. An evaluation of statistical approaches to rare variant analysis in genetic association studies. Genetic Epidemiology. 2010
Zhao SS […] Bowes J. Genetically proxied interleukin-13 inhibition is associated with risk of psoriatic disease: Mendelian randomization study. Arthritis & Rheumatology. 2024
Zhao SS […] Bowes J. Association of lipid-lowering drugs with risk of psoriasis: a Mendelian randomization study. JAMA Dermatology. 2023
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