Denis Evseenko, M.D., Ph.D., associate professor of orthopedic surgery, and stem cell and regenerative medicine at the Keck School of Medicine, University of Southern California, is the proud recipient of a $3.4 million grant from the National Institute of Health (NIH) to fund his research into the development, progression and prevention of osteoarthritis (OA).
NIH to Fund Novel $3.4 Million OA Study
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Another grant from the Department of Defense for $750,000, will fund pre-clinical research on novel drug candidates that may have the potential to regenerate cartilage and slow the progression of the disease.
The grants reflect the seriousness of the problem presented by osteoarthritis to the nation’s public health.
Caused by injuries and everyday wear and tear, osteoarthritis, is the most common joint disorder in the United States. Its prevalence is steadily growing due to longer life spans and increased obesity rates. It is estimated that by 2032, nearly 30% of people age 45 and older will be diagnosed with the disease.
There is no cure.
Evseenko hypothesizes that genetic and pharmacologic manipulation of the body’s glycoprotein 130 (gp130) receptor molecule could decrease the effects of arthritis by slowing cartilage degradation or by building new cartilage.
If the pre-clinical research data holds true, he hopes to launch clinical trials for an injectable therapy that would delay the progression of arthritis among those in early stages of the disease.
According to Dr. Evseenko, “Osteoarthritis is a looming public health problem with few solutions on the horizon. With these concurrent research efforts, we hope to translate our foundational knowledge about joint cartilage development into clinical therapies that would improve millions of lives.”
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This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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