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A new study has been conducted by researchers at Linköping University in Sweden on multiple sclerosis. They identified a combination of 11 proteins that can predict disease activity and disability outcomes in MS patients. In MS, the immune system attacks the body's nerves, particularly the myelin surrounding nerve axons, leading to impaired signal transmission. Disease progression varies among individuals, making it crucial to identify those requiring more aggressive treatment early on.
The study involved analyzing nearly 1,500 proteins in samples from 92 individuals with suspected or recently diagnosed multiple sclerosis. Machine learning models used the data, combined with patient information such as disability levels, MRI results, and treatments, to identify proteins predicting disease progression. The researchers narrowed down the panel to 11 proteins, making it a more cost-effective and feasible analysis for future applications. The researchers emphasize the importance of measuring these proteins in cerebrospinal fluid. They found it better reflects central nervous system activity compared to blood measurements.
Additionally, the study identified neurofilament light chain (NfL), a protein leaking from damaged nerve axons, as a reliable biomarker for short-term disease activity. A separate group of MS patients validated these findings.
The study is notable for utilizing a highly sensitive method, proximity extension assay combined with next-generation sequencing (PEA-NGS), allowing accurate measurement of proteins even in small amounts, crucial as these proteins are often present in low levels. The identified proteins could potentially be used to tailor treatments based on individual disease severity in MS patients.
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