Towards Risk Stratification for RA in a First Degree Relative (FDR) cohort; The PRe-clinical EValuation of Novel Targets in RA (PREVeNT RA) cohort

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory arthritis affecting 1% of the UK adult population and is associated with significant morbidity and mortality. The development of RA is not fully understood although we do know that genetic and environmental risk factors both contribute. The current paradigm is that individuals progress through phases of genetic susceptibility and systemic autoimmunity to symptoms without clinical disease and on to unclassified arthritis before developing definite RA. A major challenge now is to better understand how we can classify unaffected individuals according to levels of risk and identify the early steps in developing autoimmunity. Doing so would also offer the potential to predict and prevent and cure RA and provide an exemplar approach to follow in other auto-immune diseases.

We have recruited a national cohort of first-degree relatives (FDRs) of existing RA patients into the PRe-clinical EValuation of Novel Targets in RA (PREVeNT RA) study. This programme aims to study risk factors and early preclinical disease in RA-free individuals. To date, 3000 people have been recruited with data collected on lifestyle questionnaires, blood for autoantibodies and high sensitivity CRP.

The Objectives of this PhD are to:
A: Undertake a systematic review of current literature around risk prediction for development of RA.
B: Characterise the PREVeNT RA cohort in terms of their genetics, environmental risk factors and systemic autoimmunity.
C: Compare the PREVeNT RA cohort to a general population of primary care consulters with particular focus on joint symptoms and existing co-morbidities (autoimmunity and cardiovascular risk).
D: Determine which joint symptoms are associated with a higher risk of developing RA (defined on the basis of lifestyle, serology and MSK ultrasound).

Entry Requirements
Applicants are expected to hold, or about to obtain, a minimum upper second class undergraduate degree (or equivalent) in biomedical sciences, genetics, statistics/mathematics or a related scientific discipline. A Masters degree in a relevant subject and/or experience in biomedical sciences, genetics, statistics/mathematics or a related scientific discipline is desirable.