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Improved classification of myositis disease subtypes using statistical genetics approaches for stratified medicine

Project Description

Keywords: idiopathic inflammatory myopathy, myositis, genetics, disease classification, stratified medicine

Idiopathic inflammatory myopathies (IIM) are heterogeneous autoimmune diseases characterized by inflammation of skeletal muscle (myositis). Other organ involvement due to lung, heart and skin disease and cancers can lead to increased mortality. IIM is difficult to diagnose, classify and treat; many patients are permanently disabled due to irreversible muscle damage. Improved disease classification in IIM is vital to stratify patients to improve disease management and enable earlier, more targeted treatment.

In this PhD project, we aim to improve disease classification and characterise disease subtypes in IIM. The student will aim to identify genetic risk factors that differentiate disease subgroups; to investigate similarities and differences in genetic risk factors between IIM and related immune-mediated inflammatory disorders, and to use publically available genetic and genomic data to increase understanding of different types of myositis.

The student will use a number of statistical genetics approaches to exploit our wealth of clinical, genetic, genomic and autoantibody data to improve patient stratification. These approaches may include polygenic risk score analysis, conditional false discovery leveraging other autoimmune diseases, meta-analyses, Mendelian randomization, machine learning and integrated multi-omics approaches.

We expect these analyses to improve disease classification and our ability to stratify patients in IIM. This may improve our understanding of the pathogenesis and disease mechanisms in different forms of IIM. This research also will improve the evidence-base for stratified medicine, leading to more focussed disease management and treatment.

The student will be integrated into an active research group within the Versus Arthritis Genetics and Genomics Centre of Excellence. Training will be provided in quantitative statistical genetics skills, and interdisciplinary skills in translational and stratified medicine. There will be opportunities to attend and present results at national and international meetings and conferences, and public and patient engagement events.

Manchester Myositis Research Group:

Entry Requirements:
Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a biomedical science or statistics related subject. A Masters qualification in a similar area would be an advantage. Candidates with experience or with an interest in autoimmune disease and/or genetics are encouraged to apply.

For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit

Funding Notes

Applications are invited from self-funded students. This project has a Band 1 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy 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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