A recent study suggests that a basic blood test could help identify knee osteoarthritis in people who have not yet had any symptoms. This detection could occur up to eight years before changes to their bones become apparent on an X-ray, scientists say.
In this research, scientists examined blood samples from 200 white women who initially had no signs of osteoarthritis and were considered “low risk” for developing the disease based on traditional risk factors such as injury. or previous knee surgeries.
Using the new test, which focuses on analyzing proteins in the blood to predict individual risk, the researchers assessed the same participants. They found that the risk of developing knee osteoarthritis within ten years could be accurately predicted using just six blood-borne proteins. This discovery was detailed in a study published in the journal Science Advances.
In some cases, the test has the potential to predict the disease eight years before the signs seen on an X-ray, which marks a notable advancement given that X-rays are currently the primary diagnostic tool for osteoarthritis. Researchers emphasize the importance of early detection, emphasizing that while there is no cure for the disease, there are preventative strategies to slow its progression. These strategies involve lifestyle adjustments, such as participating in low-impact physical activities, weight management, and using medications to relieve symptoms.
Dr. Virginia Byers Kraus, lead author of the study and professor of medicine at Duke University in North Carolina, suggests that early identification of osteoarthritis could serve as a “wake-up call” to encourage individuals to adopt preventive therapies. These measures could potentially prevent the development of later complications such as pain, disability and the need for joint replacements.
In the future, the research results could contribute to the development of improved preventative treatments for osteoarthritis. Dr. Kraus speculates that these treatments could target specific proteins in the bloodstream linked to the disease, providing more effective prevention options.
Osteoarthritis, which affects more than 32.5 million adults in the United States, is the most common type of arthritis. Originally nicknamed “wear and tear,” it occurs when the cartilage in a joint, typically found in the hands, hips and knees, deteriorates. Consequently, this breakdown leads to alterations in the underlying bone, leading to feelings of pain, stiffness and swelling.
Yet emerging evidence now indicates that inflammation plays a crucial role in the joint deterioration seen in osteoarthritis. This suggests the potential existence of “biomarkers,” measurable indicators in the body, that could signify the onset of disease long before structural damage is detected by X-rays.
In a recent study, Kraus and his team examined two sets of blood samples from a well-established group of middle-aged white women in the United Kingdom. These women have been regularly evaluated for their osteoarthritis since 1989. From this group, 200 women were selected based on their age and body mass index (BMI). Over a 10-year period, half of these women were diagnosed with osteoarthritis while the other half were unaffected.
Using artificial intelligence, researchers identified six proteins in blood samples that seemed to indicate the likelihood of developing osteoarthritis. These blood samples were taken eight or four years before the individuals were diagnosed with the disease. The identified proteins are associated with the initiation of inflammation and are involved in hemostasis, which is an initial step in the body’s response to injury.
To assess the accuracy of the test, the team used a statistical measure known as area under the curve (AUC). An AUC value of 50% or less suggests that the test cannot effectively distinguish individuals with and without the disease. A value above 70% is considered “acceptable” performance, while anything above 80% is considered “excellent”. In this study, all six proteins gave an AUC of 77%. This figure is significantly higher than predictions based solely on age and BMI (around 50%) or knee pain (around 57%).
Implementation of this test in the clinic is not imminent, despite promising initial results, according to Kraus. The research team now needs to determine whether these findings can be replicated in men and individuals from diverse ethnic backgrounds. Osteoarthritis is more common in women, especially after age 50.
Kraus mentioned that as a result of this, there could be potential clinical trials for new treatments. These biomarkers could serve as indicators to assess whether specific medications can stop the progression of osteoarthritis. If these trials prove conclusive on animal models, the drugs could then be tested on individuals at risk of developing the disease.
