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| Funder | Versus Arthritis |
|---|---|
| Recipient Organization | University College London |
| Country | United Kingdom |
| Start Date | Jan 01, 2023 |
| End Date | Dec 31, 2027 |
| Duration | 1,825 days |
| Number of Grantees | 1 |
| Roles | Award Holder |
| Data Source | Europe PMC |
| Grant ID | 22977 |
Rheumatoid Arthritis is a common, and severe autoimmune disorder effecting 1% of the UK. Diagnosis is commonly after 50-years old, and early management is vital to preventing chronic damage in patients. Delayed diagnosis cause increased joint inflammation and lower quality of life in patients.
No-where in RA is this more pronounced than Seronegative RA (SNRA), these patients lack the classical autoantibodies for RA and consequently their diagnosis and treatment is significantly delayed.
Prompt treatment for RA is vital for good disease management and delays give a greater risk of failing to respond to treatment.
Approximately 30% of RA patients are seronegative and thus have delayed diagnosis resulting in worse disease at presentation. It is therefore vital to find new methods of diagnosing these patients to enable prompt management.
Management in RA is complicated with no single method of predicting response or failure to first line treatment, similarly for SNRA patients some treatments such as Rituxumab are effective in small studies but not considered as SNRA patients lack the traditional autoantibodies against citrullinated peptides (aCCP) or Rheumatoid factor (RF).
My project aims to enrich the diagnostic tools for RA, specifically targeting SNRA patients, and to improve stratification and prediction to response whilst gaining a deeper understanding of the pathogenic mechanisms which drive RA.
Initially I will use antigen detection methodologies in SNRA and other RA subgroups, to detect novel autoantibodies in these patients.
These autoantibodies will then be screened for use as a diagnostic tool in SNRA and other RA phenotypes, will then be analysed against clinical information to aid in patient stratification resulting in optimal treatment.
Secondly I will apply advanced biophysical methodologies to novel and known antigens in RA to understand why patients develop autoantibodies gaining a deeper understanding of the underlying pathogenic mechanisms in RA.
University College London
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