People Identified at High-Risk of Developing Rheumatoid Arthritis

According to the study’s lead researcher, Dr. Ian Scott, department of genetics & molecular medicine at King’s College London, this new prediction modeling technique can also identify people at risk of developing rheumatoid arthritis at a younger age.

"This new computer-based technique of prediction modeling allows us to estimate someone’s risk of developing rheumatoid arthritis over their lifetime using genetic markers from a single blood test and information about their smoking habits," explained Dr. Scott.

"I hope that, as we understand the risk factors for rheumatoid arthritis better, our prediction modeling method could be used to screen people for this disease before they develop any symptoms. This is an important first step in trying to develop ways to prevent the onset of rheumatoid arthritis."

"Within the general population, few individuals that have clinically significant increased risks are likely to be identified using this approach. But targeted screening of people already at an increased risk of rheumatoid arthritis, such as relatives of patients, could identify enough high-risk people to allow researchers to look at ways to prevent rheumatoid arthritis from developing."

Individuals classed as being high risk, using information from the most important gene associated with rheumatoid arthritis (the HLA-DRB1 gene), are more likely to develop rheumatoid arthritis at a younger age. They could be monitored for early signs of the disease. Treating rheumatoid arthritis early, before significant joint damage has occurred, increases the likelihood that the individual will go into remission (no joint pain or swelling) following treatment.

Identifying people who are at a very high-risk of developing rheumatoid arthritis can also provide a better understanding of the changes in the body’s immune system that lead to rheumatoid arthritis. This could lead to the development of new treatments that target the very earliest phase of the disease.

Rheumatoid arthritis is an autoimmune condition that causes pain and inflammation in the joints. It affects around 400,000 people in the UK and is at present incurable. Many factors are known to contribute to an individual’s risk of developing rheumatoid arthritis. These are divided into two categories: inherited genetic factors (46 genetic risk factors have been identified that increase someone’s risk of developing rheumatoid arthritis) and so called “environmental” factors such as smoking.

The new computer-based technique of prediction modeling allows researchers to combine both genetic and environmental risk factors to estimate an individual’s lifetime risk of developing this disease.

According to the study’s lead researcher, Dr. Ian Scott, Department of Genetics & Molecular Medicine at King’s College London (United Kingdom), this new prediction modeling technique can also identify people at risk of developing rheumatoid arthritis at a younger age. “Within the general population, few individuals that have clinically significant increased risks are likely to be identified using this approach. But targeted screening of people already at an increased risk of rheumatoid arthritis, such as relatives of patients, could identify enough high-risk people to allow researchers to look at ways to prevent rheumatoid arthritis from developing.” This research is published in PLoS Genetics, September 19, 2013.

Individuals classed as being high risk, using information from the most important gene associated with rheumatoid arthritis (the HLA-DRB1 gene), are more likely to develop rheumatoid arthritis at a younger age. They could be monitored for early signs of the disease. Treating rheumatoid arthritis early, before significant joint damage has occurred, increases the likelihood that the individual will go into remission (no joint pain or swelling) following treatment.

Identifying people who are at a very high-risk of developing rheumatoid arthritis can also provide a better understanding of the changes in the body’s immune system that lead to rheumatoid arthritis. This in turn could lead to the development of new treatments that target the very earliest phase of the disease.

Dr. Scott added that as knowledge of the genetic and environmental risk factors that cause rheumatoid arthritis increases, it will improve the accuracy with which it is possible to predict an individual’s chance of developing this disease, and allow researchers to investigate new ways to stop it in its tracks before any symptoms develop.

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Department of Genetics & Molecular Medicine at King’s College London