A new study conducted by researchers at Linköping University in Sweden has identified a combination of 11 proteins that can predict long-term disability outcomes in multiple sclerosis (MS) for different individuals. These proteins have the potential to be used in tailoring treatments to individuals based on the expected severity of the disease. The findings of the study have been published in the journal Nature Communications.
The researchers discovered that by measuring these 11 proteins in the cerebrospinal fluid, which better reflects the central nervous system compared to blood samples, they could predict both short and long-term disease activity and disability outcomes. This information is crucial for identifying patients who may require more powerful treatments at an early stage of the disease.
Multiple sclerosis is an autoimmune disease in which the immune system targets the body’s own tissues, causing damage to the nerves in the brain and spinal cord. Specifically, the fatty compound called myelin, which surrounds and insulates the nerve axons, is primarily attacked. This damage leads to a less efficient transmission of signals.
The progression of MS varies greatly from person to person. It is important to identify individuals who are likely to experience more severe disease outcomes so that they can receive appropriate treatment quickly. The researchers aimed to develop an analysis tool that could detect patients in the early stages of the disease who would benefit from more effective treatment options.
The study involved analyzing nearly 1,500 proteins in samples from 92 individuals with suspected or recently diagnosed MS. The researchers combined this protein data with information from the patients’ medical records, such as disability scores and results from MRI scans of the nervous system. By using machine learning techniques, the researchers were able to identify a panel of 11 proteins that could accurately predict disease progression.
One particular protein called neurofilament light chain (NfL), which leaks from damaged nerve axons, was found to be a reliable biomarker for short-term disease activity. The presence of NfL indicates how active the disease is.
The strength of the study lies in its confirmation of the protein panel’s accuracy in predicting disease outcomes across different patient groups. The combination of proteins found in the initial patient group at Linköping University Hospital was validated in another group of 51 MS patients at the Karolinska University Hospital in Stockholm.
The researchers utilized a highly sensitive method called proximity extension assay combined with next-generation sequencing to measure a large number of proteins accurately. This method allows for the measurement of even very low levels of proteins, which is crucial in the case of these markers.
The study was funded by various organizations, including the Swedish Foundation for Strategic Research, the Swedish Brain Foundation, and the Swedish Research Council.
The identification of these 11 proteins as predictors of long-term disability in multiple sclerosis brings us one step closer to tailoring treatments to individual patients based on disease severity. This personalized approach could save valuable time and resources by ensuring that patients receive the most effective treatments from the early stages of the disease. However, further research and validation are needed before these findings can be applied in clinical practice.
