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, scientists and individuals with OA (or at risk of OA) across a number of universities, pharmaceutical companies and hospitals to design this study. We will analyse the knee fluid (obtained by needle and syringe) of nearly 2000 individuals who have a diagnosis of OA or who have recently had an acute knee injury. These samples have already been collected and are stored. We will use cutting edge methods to measure over 5000 different protein molecules in each of the fluid samples and study these alongside patient reported measures such as pain and disability.
Using advanced statistical methods we will be able to address a number of key questions. We will use the signature of proteins in the knee joint fluid to ask whether OA is a single disease at the protein level, or whether there are multiple different types of OA that can be identified. We will seek common pathways which are suggested by specific proteins to identify possible novel causes of disease. We will study the relationship between different protein levels and pain to uncover new molecules that could be targeted for treatment or which could represent an objective marker (biomarker) of pain for future clinical trials. We will ask whether the protein signature at the time of joint injury predicts future development of OA.
Finally we will create 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.
Project update (JUNE 2023) 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 are linked to clinical cross-sectional data, including pain and x-ray scores
- Data analysis, dictated by Data Analysis Plan V1.0, has been carried out for the Discovery dataset
- Discovery dataset was presented at OARSI 2023
- Replication dataset is underway and should be completed end summer 2023
- QC paper describing detailed methodology is about to be submitted
Copies of the following documents can be accessed by clicking on the links.
For project enquiries please email firstname.lastname@example.org.