Genetic Differences Behind Variable Response to Rheumatoid Arthritis Drugs

Research from Queen Mary University of London suggests that the reason patients with rheumatoid arthritis often have different responses to therapy could be due to their genetic profiles.

Around 1.3 million adults are affected by rheumatoid arthritis in the U.S. There has been much progress in treating the autoimmune condition, which results in the body attacking its own joint tissue, in recent years, but around 40% of patients do not respond to specific therapies. Up to 20% of patients appear to be resistant to all current forms of treatment for the condition.

“The mechanisms of nonresponse are largely unknown and, unlike in other medical fields such as cancer where molecular pathology guides the use of targeted therapies, biomarkers able to predict response to specific agents in rheumatoid arthritis are still lacking,” write the authors in the new study published in Nature Medicine.

Costantino Pitzalis, Professor of Rheumatology at Queen Mary, and colleagues investigated differing patient responses to two common arthritis drugs, the monoclonal antibody therapies rituximab and tocilizumab via joint tissue biopsies.

The researchers included 164 arthritis patients who were involved in an earlier trial testing rituximab vs tocilizumab, which was published in The Lancet last year. The 2021 study suggested that patients with low or missing B-cell lineage expression signature in synovial tissue fared better when treated with tocilizumab. Of these patients, 50% responded to tocilizumab, but only 12% to rituximab.

In the current study, joint tissue biopsies from the patients were examined further and analyzed for genetic associations. The authors discovered genetic signatures linked with response to each drug and also highlighted a specific genetic profile, comprising 1277 genes, in tissue taken from patients who did not respond to any therapies.

“Incorporating molecular information prior to prescribing arthritis treatments to patients could forever change the way we treat the condition. Patients would benefit from a personalized approach that has a far greater chance of success, rather than the trial-and-error drug prescription that is currently the norm,” commented Pitzalis, also co-senior author of the study, in a press statement.

The team then used the data they collected to train machine learning algorithms to predict whether patients will respond to rituximab or tocilizumab and also whether they will be multi-drug resistant, which they are hoping to validate and develop further for use in the clinic.

“These results are incredibly exciting in demonstrating the potential at our fingertips; however, the field is still in its infancy and additional confirmatory studies will be required to fully realize the promise of precision medicine in rheumatoid arthritis,” said Pitzalis, also co-senior author of the study, in a press statement.

“The results are also important in finding solutions for those people who unfortunately don’t have a treatment that helps them presently. Knowing which specific molecular profiles impact this, and which pathways continue to drive disease activity in these patients, can help in developing new drugs to bring better results and much-needed relief from pain and suffering.”