Genes can help predict response to arthritis treatment

A new study led by Queen Mary University of London has shown that molecular profiling of diseased joint tissue can significantly impact whether specific drug treatments will work to treat rheumatoid arthritis (RA) patients.

The researchers also identified specific genes associated with resistance to most available drug therapies, commonly referred to as refractory disease, which could provide the key to developing new, successful drugs to help these people. Their study has been published in the journal Nature Medicine.

While there has been much progress made over the past decades in treating arthritis, approximately 40% of patients do not respond to specific drug therapies, and 5–20% of people with the disease are resistant to all current forms of medication. This led researchers to carry out a biopsy-based clinical trial, involving 164 arthritis patients, in which their responses to either rituximab or tocilizumab — two drugs commonly used to treat RA — were tested.

The results of the original trial, published in The Lancet in 2021, demonstrated that in those patients with a low synovial B-cell molecular signature only 12% responded to a medication that targets B cells (rituximab), whereas 50% responded to an alternative medication (tocilizumab). When patients had high levels of this genetic signature, the two drugs were similarly effective.

The team also looked at cases where patients did not respond to treatment via any of the drugs and found that there were 1277 genes that were unique to them specifically. Building on this, the researchers applied a data analysis technique called machine learning to develop computer algorithms that could predict drug response in individual patients. The machine learning algorithms, which included gene profiling from biopsies, performed considerably better when predicting which treatment would work best compared to a model that used only tissue pathology or clinical factors.

The study strongly supports the case for performing gene profiling of biopsies from arthritic joints before prescribing expensive biologic targeted therapies. This could save patients considerable time and money and help avoid potential unwanted side effects, joint damage and worse outcomes. As well as influencing treatment prescription, such testing could also shed light on which people may not respond to any of the current drugs on the market, emphasising the need for developing alternative medications.

“Incorporating molecular information prior to prescribing arthritis treatments to patients could forever change the way we treat the condition,” said Queen Mary’s Professor Costantino Pitzalis, who co-supervised the study. “Patients would benefit from a personalised approach that has a far greater chance of success, rather than the trial-and-error drug prescription that is currently the norm.

“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 realise the promise of precision medicine in RA.

“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.”

Image credit: ©stock.adobe.com/au/hriana

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