October 11, 2024

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Genes can predict arthritis treatment success

Genes can predict arthritis treatment success



 

Genes can predict arthritis treatment success. 

Molecular profiling of diseased joint tissue may greatly influence whether certain drug treatments are effective in people with rheumatoid arthritis (RA), according to a new study from Queen Mary University of London.

The study was published in the journal Nature Medicine on May 19, 2022 .

The researchers also identified certain genes involved in resistance to most current drug therapies, often referred to as refractory disease, which may hold the key to the search for new effective drugs to help these patients.

 

 

Although the treatment of arthritis has greatly improved over the past few decades, a large proportion (approximately 40%) do not respond to specific drug treatments, and 5%-20% of patients are resistant to all existing Drugs are resistant.

 

The researchers conducted a biopsy-based clinical study of 164 arthritis patients, testing their response to either rituximab or tocilizumab — two drugs routinely used to treat RA.

Results of the original trial, published in The Lancet in 2021, showed that only 12% of people with a low molecular profile of synovial B cells responded to B-cell-targeting therapy (rituximab), and 50% responded to another drug (tocilizumab).

Both drugs were equally effective when patients had a large number of this genetic signature.

 

As part of the first study funded by the MRC and NIHR Collaborative Efficacy and Mechanism Evaluation (EME) programme, the Queen Mary University of London team also looked at patients who did not respond to treatment with any drug and found that 1277 genes were specifically for them.

 

 

Based on this, the researchers applied a data analysis technique called a machine learning model to develop computer algorithms capable of predicting individual patient drug responses.

Machine-learning algorithms, including genetic analysis from biopsies, performed reasonably well at predicting which treatments would work best compared to models using only histopathological or clinical factors.

 

The study strongly supports the practice of genetically analyzing arthritic biopsies before prescribing expensive so-called biologically targeted therapies.

This could save the NHS and society a great deal of time and money, and help avoid potentially unwanted side effects, joint damage and worse outcomes commonly seen in patients.

In addition to influencing treatment prescriptions, the test could reveal who might not respond to any drug currently on the market, underscoring the need to develop alternative medicines.

 

Costantino Pitzalis, professor of rheumatology at Queen Mary University of London, Versus Arthritis, said: “Incorporating molecular information before prescribing arthritis treatments to patients could forever change the way we treat this disease. Patients will benefit from a personalised approach that The chances of success are much greater than the trial and error prescription of drugs that is currently regulated.”

 

“These results are incredibly exciting and demonstrate the potential at our fingertips, however, the field is still in its infancy and more confirmatory studies are needed to fully realize the promise of precision medicine in RA.”

 

“These results are also important for finding solutions for those unfortunate enough that their current treatments are not helping them. Understanding which specific molecular signatures influence this, and which pathways continue to drive disease activity in these patients, could help develop new treatments.  Medications for better outcomes and much-needed relief from pain and distress.”

 

Incorporating these features into future diagnostic tests will be a necessary step in translating these findings into routine clinical care.

 

 

 

Genes can predict arthritis treatment success

(source:internet, reference only)


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