Predict
Clinical Biomarkers
Every molecule and every cell in the immune system has a function, and together they can tell a story—past, present or future. Proven biomarkers can predict relapses, guide how therapy is working and reveal secrets of resilience that may not be evident on the surface. Powering biomarkers is the science that tells these stories, and how they can help save and improve lives.
Detect Upcoming Relapses to Stop Them Before They Occur
Relapses in NMOSD or MOGAD can cause life-changing symptoms and occur without warning. Uncertainty of a future relapse can be disabling and reduce quality of life. GJCF and its research partners are pioneering ways to predict relapses through biomarker pattern science of sera from patients in the CIRCLES study.
Understanding which biomarkers increase or decrease well in advance of a relapse can help predict a relapse so that it can be stopped before it starts.
1,250 NMOSD Patients & Controls
Clinical Visits Every 6 Mo X 7 Years
> 1M Datapoints & 100K Samples
Longitudinal Serum Samples
GJCF is a leading collaborative efforts for biomarker science to better understand anti-AQP4+, anti-MOG+ as well as seronegative disease. The CIRCLES study biorepository has been key to many of these studies. Over seven years, CIRCLES followed nearly 1,000 patients and hundreds of control individuals. Each participant had a clinical visit every ~6 months, where data regarding clinical signs and symptoms were collected. Along with these data, blood draws were performed to gather serum, T and B cells and other immune cells (also called PBMCs), as well as DNA and RNA. This one-of-a-kind blood bank collected millions of data points and over 100,000 biospecimens that have been invaluable to research that has already revolutionized our understanding of NMOSD, MOGAD and seronegative cases. Discoveries can be surprising. For example, preliminary results from our program to predict relapses suggests that some biomarkers go up before a relapse, but others go down. In other words, it may be that relapses in NMOSD and like diseases are as much about loss of immune system brakes as they are increases in the inflammation gas pedal. Stay tuned—GJCF is powering biomarker science.
Applying Predictive Medical Science
The science of predictive medicine is entering a new era based on big data analyses, artificial intelligence and machine learning. These new mathematical and statistical modeling methods now enable far greater precision to forecast events and outcomes in many important areas of medicine. From predicting relapses to personalizing best treatment outcomes, the ability to accurately predict the future is a bold new frontier in NMOSD and MOGAD (MOG Antibody Disease). For example, relapse prediction can prompt proactive treatment to stop the relapse before it occurs. This is a GJCF mission goal.
Reduce Risks of Relapses or Stop Them Quickly if They Occur
Approved medicines offer a best chance to minimize relapse risks. Now GJCF is driving new treatments to stop relapses in their tracks if they do occur.