Osteoarthritis Serial Ubiquitin Multiome (OA-SUMome) discovery pipeline: A versatile approach for OA patient stratification and therapeutic target identification
More than 10 million people in the UK live with osteoarthritis, yet the only treatment for advanced disease is a knee replacement. Researchers have discovered that after a joint injury, enzymes that remove protein tags called ubiquitin become hyperactive in cartilage, driving chronic inflammation and tissue damage. This project will profile those "ubiquitin-removing" enzymes in cartilage and joint tissue from patients undergoing knee surgery, using artificial intelligence to group patients by their enzyme activity patterns and disease stage. If successful, this work could replace the one-size-fits-all approach to osteoarthritis with personalised therapies that target the root cause of tissue damage rather than just managing symptoms. By identifying which drug compounds block these enzymes, the team aims to repurpose existing approved drugs for clinical trials. The research also uses gene-editing to study what happens when these enzymes are absent, revealing how they control normal cartilage and bone function. This is translational science with a clear path to patient benefit: better patient stratification, more effective targeted treatments, and reduced healthcare costs from a disease that is the leading cause of disability worldwide.
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Importance Osteoarthritis (OA) is a widespread disease causing chronic joint pain and stiffness, making it the leading cause of disability worldwide. Affecting over 10 million people in the UK, it significantly impacts the ability to work and enjoy daily activities, often leading to isolation and a poor quality of life. OA is also associated with other chronic conditions like heart disease and diabetes, complicating treatment and increasing healthcare costs. Currently, knee replacement is the only available treatment. To improve treatment, we have developed a new method using biological approaches to better categorise OA patients and identify optimal treatment targets. This will help understand how OA affects individuals differently and design tailored treatments to meet each patient's specific needs, leading to more effective and personalised care. Background Osteoarthritis is triggered by mechanical injury to joint cartilage, leading to pain and inflammation. If the tissue doesn’t heal properly, it can cause ongoing inflammation, damage, and loss of function, resulting in OA. Recently, we discovered that after an injury, certain changes occur in cells, including the addition or removal of protein markers/tags called ubiquitin molecules. These changes can lead to chronic inflammation and worsen tissue damage. We found that enzymes responsible for removing these ubiquitin tags are highly active in injured and osteoarthritic cartilage. These "ubiquitin removers" are believed to drive ongoing inflammation in OA, with their activity linked to tissue damage and disease progression. My ultimate goal My goal is to transform osteoarthritis treatment by identifying and targeting specific biological markers, particularly ubiquitin-removing enzymes that worsen tissue damage and inflammation. By understanding unique enzyme activity profiles in OA patients, we can develop personalised therapies that not only relieve symptoms but also address the root causes of the disease. This approach promises to improve the quality of life for millions and reduce OA's broader health impacts and costs. Key questions Can we identify specific signatures of active ubiquitin-removing enzymes in patients to tailor more effective treatments? Can we stop cartilage damage by targeting these enzymes' activity? How does the absence of these enzymes affect cartilage and bone function and development? Which approved drug compounds can block these enzymes' activity? Work plan and impact This research could change the way osteoarthritis is treated using approaches that could facilitate developing personalised treatments. By profiling active ubiquitin-removers enzymes in the cartilage and synovium tissues of OA patients after knee surgery, we can better group patients and tailor their treatments. Using artificial intelligence tools, patients will be grouped based on these profiles and disease stages, helping to personalise treatments. We will also study the effects of targeting these enzymes on tissue damage and OA development in disease models using inhibitors and gene-editing technology. Advanced imaging techniques will examine skeletal system function and inflammation. Our study will pave the way for pre-clinical and clinical trials, supported by collaborations with academics, pharmaceutical companies, and clinicians to facilitate creating more effective, targeted therapies that improve patient outcomes, reduce healthcare costs, and lessen OA's broader health impacts.
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