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Serum Protein Biomarkers Can Predict Worsening Knee Osteoarthritis

NEW YORK — Researchers have teased out a suite of serum biomarkers that can predict whether someone's knee osteoarthritis will worsen over time.

Knee osteoarthritis affects about 10 percent of men and 13 percent of women over the age of 60 and can cause disability. Factors like age, sex, body mass index, and radiographically determined severity are typically used to gauge knee osteoarthritis progression, but they are not always accurate.

A lack of biomarkers to predict those at risk of worsening knee osteoarthritis has hampered the development of treatments for the condition, according to researchers led by Duke University School of Medicine's Virginia Byers Kraus. In their new study, appearing in Science Advances on Wednesday, the researchers uncovered a set of 15 serum proteomic markers that could distinguish progressors from non-progressors.

"Therapies are lacking, but it's difficult to develop and test new therapies because we don't have a good way to determine the right patients for the therapy," Kraus said in a statement. "In the immediate future, this new test will help identify people with high risk of progressive disease — those likely to have both pain and worsening damage identified on X-rays — who should be enrolled in clinical trials. Then we can learn if a therapy is beneficial."

The investigators developed a targeted multiple reaction monitoring (MRM) proteomic panel using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to analyze blood serum samples from 596 individuals from a cohort of the Foundation for the National Institutes of Health (FNIH). In all, they analyzed 107 peptides representing 64 proteins.

At baseline, most of the participants had moderate to severe knee osteoarthritis, as determined by radiographic analysis and pain scores. Based on changes from that baseline, the researchers placed study participants in different progressor categories: those with increased radiographically determined joint space loss (JSL) and pain; those with only increased JSL; those with only increased pain; and those with neither increased JSL nor additional pain.

By comparing these groups, the investigators homed in on 15 biomarkers that distinguished the group with both increased JSL and pain from the three other groups. They additionally found biomarkers that distinguished JSL-only progressors from non-progressors and pain-only progressors from non-progressors and noted that some of these biomarkers overlapped between the groups.

Three proteins — VTDB, CRAC1, and C1R — contributed peptides to different models of essential biomarkers, the researchers found. Those proteins are involved in vitamin D availability, the extracellular matrix, and the complement system of the innate immune system, respectively.

Kraus and her colleagues focused on a set of 15 serum proteome markers representing 13 proteins that could distinguish 73 percent of the progressors from non-progressors in the FNIH cohort.

In a separate Biomarker Factory cohort of 86 individuals, this biomarker set could distinguish 70 percent of progressors. However, the researchers noted that this cohort was small. Also, since two of the biomarkers had not been measured in this group, they had to rely on alternative markers known to correlate with those two missing ones.

Overall, the performance of the biomarkers was better than that of traditional predictors based on structural osteoarthritis and pain severity, and better than urinary carboxyl-terminal cross-linked telopeptide of type II collagen, which had previously been tied to osteoarthritis progression. Those approaches can distinguish 59 percent and 58 percent of progressors, respectively, according to the researchers.

"In addition to being more accurate, this new biomarker has an additional advantage of being a blood-based test," Kraus said. "Blood is a readily accessible biospecimen, making it an important way to identify people for clinical trial enrollment and those most in need of treatment."

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