Protein Biomarker Identified for MS May Predict Disease Severity, Treatment Response

Protein Biomarker Identified for MS May Predict Disease Severity, Treatment Response

A newly discovered potential biomarker of multiple sclerosis (MS) may help to distinguish between people who will go on to have less severe disease and those in whom the disease will progress, researchers at Linköping University in Sweden report. The biomarker’s discovery came through an investigation into the immune system of MS patients, which behaves differently in these people than it does in those without the disease.

The researchers’ study, “Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis” published in the journal Cell Reports, may lead to a test able to assist in patient management.

Biomarkers are naturally occurring substances, in the blood or elsewhere, that are measurable indicators of conditions or diseases, and aid in diagnosis, or in judging a patient’s response to treatment and likely disease progression. Because people with MS, a chronic inflammatory disease of the central nervous system, have a widely differing responses to treatment and levels of disease severity, biomarkers would be of considerable aid in treating these patients. But research into MS biomarkers has been hampered by the complexity of the disease process, whose underlying mechanisms reflect the interplay between a large number of genes and their downstream targets, the team said in a news release.

Researchers compared the gene expression in immune cells from patients with MS to immune cells from healthy controls, to identify relevant genes that might translate into clinically valuable MS biomarkers. They focused on CD4+ T-cells, because these are early and important regulators of adaptive immunity, a complex and antigen-specific (or foreign antibody-specific) immune response.

In a series of experiments, the researchers tested how large numbers of proteins interact with each other and, using bioinformatics, sought to discover those proteins that are highly significant in MS, behaving differently in patients than in controls upon activation.

The biomarker discovered combines four proteins, and the combination of these proteins, as measured in cerebrospinal fluid (CSF), distinguished MS patients and healthy controls. Importantly, researchers were able to determine those patients who would have active disease two years later and, using small group of MS patients, response to Tysabri (natalizumab), a common treatment.

“A key finding is that a combined protein score of CXCL1-3, CXCL10, CCL2, and OPN, measured in CSF, was able not only to discriminate early MS from controls … but also to predict evidence of disease activity after 2 years, a most valuable finding when deciding treatment strategies,” the researchers wrote. “Of note, the combined score … was also able to predict low or high response to treatment, which suggests that proteins relevant to the disease process are also important for the response to treatment, further strengthening the potential use of the combined score in personalized treatment.”

 

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