TR: What does this work add to the goal of preventing RA before clinically active disease ensues? How far off do you think we are from achieving that goal?
Dr. Firestein: One of the challenges with RA prevention is that the markers for identifying at-risk individuals are not specific enough to make therapeutic decisions. A positive anti-CCP test is helpful, but only about a third of those people will ultimately transition to clinical RA. Therefore, testing therapeutic agents for prevention is difficult because most of the patients will never develop the disease.
Our new data can provide insights that will hopefully lead to better biomarkers that identify those individuals at the greatest risk. In addition, the pathways identified could help us identify which agents might work the best in those individuals. We know that there is a diversity of responses to targeted treatments, and we currently rely on trial and error for optimizing therapy. If we understand the mechanisms of disease for an individual, we might be able to tailor the therapy more precisely.
TR: This study looked at ACPA-positive individuals. Are we any closer to understanding the immunobiology of seronegative RA?
Dr. Firestein: We have typically viewed seronegative RA as a different disease, with distinct pathogenic mechanisms and genetics. Even though the distribution of joints, clinical presentations and responses to some therapies can be similar, we would need to do a separate study with the seronegative group to understand its trajectory and pathways.
TR: What research needs to be done next?
Dr. Gillespie: We need a deeper understanding of the molecular mechanisms that control the development of autoimmune diseases. Specifically in RA, we need to understand what is driving differences in ACPA-positive individuals who transition to clinical RA and in those who do not transition. It’s likely there are multiple routes to get to clinical disease, which emphasizes the importance of developing new integrative omics technologies.
It’s also important for us to validate these findings and predictions in new cohorts, such as StopRA: National. As mentioned earlier in this interview, understanding mechanisms leads to more precise therapies and better predictive models.
Conclusion
Take a look at the incredible website—complete with interactive tools—that accompanies this
work: https://apps.allenimmunology.org/aifi/insights/ra-progression.
Thanks to this work, we’re many steps closer to understanding why seropositive RA develops and what we might do to prevent it. Inflammatory disease begins well before we see synovitis on exam, and a better understanding of what’s brewing before the storm could lead to the development of preventive therapies. We look forward to big data research from this group and others in the near future.
