• Research

    Advancing precision and predictive medicine in rheumatoid arthritis

By Alumni Magazine

Most patients who are diagnosed with rheumatoid arthritis respond to either the first or second line of drug therapies. However, some patients try multiple drugs without improve ment in their condition. It can take as long as two years of suffering, disease progression and expense before landing on a medication they respond to.

John Davis III, M.D.Division of Rheumatology at Mayo Clinic in Rochester, says that’s not tailoring the right drug to the right person early enough. Dr. Davis is a professor in the Mayo Clinic College of Medicine and Science.

John Davis, III, M.D.

In an effort to shorten the interval to more effective treatment, Dr. Davis is studying the influence of the gut microbiome on the course of rheumatoid arthritis and response to treatment. His research aims to identify features in the microbiome that are associated with and predictive of changes in disease symptoms after therapy. A recent study on which he is co-senior author, published in Genome Medicine, found that the gut microbiome is indicative of whether or not patients will show minimum clinically important improvement in rheumatoid arthritis symptoms. It was the first study that used gut microbiome data to predict clinical improvement in rheumatoid arthritis disease activity independent of the patient’s condition or prior treatment.

“We’re trying to develop new biomarkers based on profiles of gut microbes that will enable us to predict who will respond to one drug versus another,” says Dr. Davis. “The gut microbiome is highly dynamic and reflective of a patient’s current state and history. The results of our exploratory study suggest that profiles based on the gut microbiome will tell better than any other clinical predictor how someone will do clinically in six to 12 months.”

Dr. Davis, his research collaborator Jaeyun Sung, Ph.D.Department of Surgery, co-senior author of the study and an assistant professor in the Mayo Clinic College of Medicine and Science, and their team performed a comprehensive genomic analysis on stool samples of patients with rheumatoid arthritis at two separate clinical visits. The team investigated the connection between the gut microbiome and the smallest meaningful changes in clinical disease activity and found several traits of the gut microbiome linked to prognosis.

Jaeyun Sung Ph.D.

“We observed significantly different microbiome traits between patients who eventually showed improvement and those who did not,” says Dr. Davis. “Using deep learning artificial intelligence (AI), we examined if we could predict whether a patient would achieve clinical improvement. The predictive performance resulted in 90% accuracy, demonstrating the proof of concept that the integration of gut microbiome and AI could be an avenue to predict disease course in rheumatoid arthritis.”

The researchers hope the biomarkers will inform precision medicine in the clinic. They envision a future state in which assessing the gut microbiome is a part of a patient’s workup, helping clinicians determine which medication to select. They also would like to develop a screening test to identify rheumatoid arthritis as early as possible.

Dr. Sung says the response to this research from the patients with rheumatoid arthritis, rheumatologists and scientific communities is one of the biggest he’s seen in his career. “We’re not yet ready to make an impact on the practice, but we’re on the path to advancing precision and predictive medicine — utilizing microbiome data and learning how to intervene on and impact the gut microbiome to improve chronic disease.”

Dr. Davis notes that their clinical findings, when combined with AI, may have a huge impact on the way treatment is delivered in the decades to come. “We expect our work to be a cornerstone for a new suite of omics data-based clinical tools to aid in the early detection, diagnosis, prognosis and treatment of rheumatoid arthritis.

“When a patient comes in with symptoms, we’ll be able to use all types of omics data to determine if they’re at risk for rheumatoid arthritis, which subtype of the condition they have if they have the disease, and predict when their condition will flare up, when they need to be seen by a physician and when we need to be aggressive with their treatment. This could revolutionize how we deliver care to patients. Much remains to be done, but we’re on the right path toward advancing our understanding of this disease and to individualizing medicine for patients.”

This article was originally published in Alumni Magazine, 2022, issue 3.

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