Osteoarthritis (OA) affects millions of people worldwide, yet we have limited understanding of what causes it and how to select the right drugs to treat it. In addition, OA is highly variable between individuals: some will stay stable for many years with modest pain and disability, yet others will progress over time and require surgical joint replacement. Joint injury also predisposes to the development of OA even in younger individuals, but this risk is also unpredictable. Being able to predict development or progression of disease and identify distinct or shared molecular causes of disease is vital for developing and testing new treatments.
STEpUP OA is a large international effort to attempt to answer some of these questions. We have assembled a group of doctors, researchers and individuals with OA (or at risk of OA) across a number of universities, pharmaceutical companies and hospitals to design this study. We have analysed the knee fluid (obtained by needle and syringe) from nearly 1800 individuals who have a diagnosis of OA or who have recently had an acute knee injury. We have used cutting edge methods to measure over 7000 different protein molecules in each of the fluid samples and study these alongside patient factors such as pain, x-ray disease severity, disability, age, and sex.
Using advanced statistical methods we have addressed a number of key questions.
- Using the signature of proteins in the knee joint fluid, we have examined whether OA is a single disease at the protein level, or whether there are multiple different types of OA. We found that there were no distinct types of OA based on synovial fluid molecular profiles
- We have identified common pathways driven by specific proteins that are important in OA progression
- We have studied the relationship between different protein levels and pain to uncover new molecules that may be potential analgesic targets which could also represent objective markers (biomarkers) of pain for future clinical studies.
Project update (December 2024) and expected timeline
- Over 1800 synovial fluid samples have been analysed by SomaLogic
- All samples were analysed as a single batch on the V4.1 SomaScan (meaning >7,000 proteins)
- All samples have been linked to clinical cross-sectional data, including pain and x-ray scores and demographic data
- Our procedure for normalising SOMAlogic synovial fluid proteomic data is now published and open access at PlosOne.
- All data analyses, dictated by Data Analysis Plan V1.0, are now complete for the Discovery,Replication and Combined datasets
- The Primary STEpUP OA Manuscript which examines whether there are detectable distinct molecular endotypes in knee OA using synovial fluid (SF) is submited for publication, and is available as preprint on MedRxiv.
FUTURE WORK & APPLICATIONS FOR DATA ACCESS:
STEpUP OA is a rich data set that can be used by the broader OA community to enhance OA research internationally and facilitate the development of new drugs for those with or at risk of OA. Access to those outside consortium will open upon publication of the primary manuscript.
CURRENT INTERNAL PROJECTS:
1) “Does the protein signature at the time of joint injury predicts future development of OA?”(lead: Dr Fiona Watt, Imperial College)
2) “Exploring changes in synovial fluid protein upon surgical joint distraction” (leads: Professor Vincent and Dr Perry, UK)
3) “Identification of cartilage damage candidate plasma biomarkers” (leads: Dr Mitchelmore, Novartis)
4) “Characterizing the compensatory status of the synovium in adult knee OA” (leads: Associate Professor Appleton, Canada).
Copies of the following documents can be accessed by clicking on the links.
- STEpUP OA Quality Assessment Plan
- Discovery Analysis plan
- Replication Analysis plan
- QC paper preprint
- Primary STEpUP OA preprint
- STEpUP OA Dataset variables summary
For project enquiries please email stepupoa@kennedy.ox.ac.uk.
Meet the team
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Tonia Vincent
Professor of Musculoskeletal Biology & Honorary rheumatologist
tonia.vincent@kennedy.ox.ac.uk
+44 (0)1865 612645
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Thomas Perry
Senior Molecular Epidemiologist
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