Discovery: 11 Proteins can Predict Long-Term Disability in Multiple Sclerosis

A recent study conducted by researchers at Linköping University in Sweden has identified 11 proteins that can accurately predict the long-term disability outcomes in individuals with multiple sclerosis (MS). These proteins could potentially be used to personalize treatment plans based on the expected severity of the disease.

The study, titled “Proteomics reveal biomarkers for diagnosis, disease activity and long-term disability outcomes in multiple sclerosis,” was published in the journal Nature Communications.

According to Julia Åkesson, a doctoral student at Linköping University and the University of Skövde, “A combination of 11 proteins predicted both short and long-term disease activity and disability outcomes. We also concluded that it’s important to measure these proteins in cerebrospinal fluid, which better reflects what’s going on in the central nervous system, compared with measuring in the blood.”

In multiple sclerosis, the immune system mistakenly attacks the body’s own tissues, resulting in damage to the nerves in the brain and spinal cord. Specifically, the protective myelin coating around nerve fibers is targeted, leading to decreased efficiency of signal transmission.

The progression of multiple sclerosis varies significantly from person to person. Therefore, it is crucial to identify individuals who are at a higher risk of experiencing a more severe disease. This way, they can receive appropriate treatment promptly, without wasting valuable time.

The collaboration between Linköping University, the Karolinska Institute, and the University of Skövde aimed to develop a tool that could detect, at an early stage, which patients would benefit from more potent treatment options. However, Mika Gustafsson, a professor of bioinformatics at Linköping University, emphasizes that while this discovery brings us closer to such an analysis tool, it is important to consider the potential side effects and cost of more intensive treatments. Not all patients may require them.

Overall, the identification of these 11 predictive proteins opens up new possibilities for personalizing treatment approaches for individuals with multiple sclerosis, ensuring that they receive the most effective and appropriate care for their specific condition.

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