Home Medizin Einsatz von maschinellem Lernen zur Vorhersage des Krankheitsverlaufs bei Multipler Sklerose

Einsatz von maschinellem Lernen zur Vorhersage des Krankheitsverlaufs bei Multipler Sklerose

von NFI Redaktion


A study conducted by researchers at Linköping University in Sweden, published in the journal Nature Communications, has found that a combination of only 11 proteins can predict long-term disability outcomes in multiple sclerosis (MS) for different individuals. These identified proteins could potentially be used to tailor treatments to the expected severity of the disease.

„A combination of 11 proteins was found to predict both short- and long-term disease activity and disability outcomes. We also concluded that it is important to measure these proteins in the cerebrospinal fluid as this better reflects what is happening in the central nervous system compared to measuring in the blood,“ said Julia Åkesson, a doctoral student at Linköping University and the University of Skövde.

Multiple sclerosis is a disease in which the immune system attacks the body, damaging nerves in the brain and spinal cord. An important finding of the study is the potential to predict the severity of the disease in its early stages, allowing for early intervention and more effective treatment.

The researchers analyzed nearly 1,500 proteins in samples from 92 individuals with suspected or recently diagnosed MS and found that a panel of just 11 proteins could predict disease progression. One protein, NfL, which is released from damaged nerve axons, was found to be a reliable biomarker for disease activity in the short term.

Most importantly, the identified protein combination was validated in a separate group of MS patients, confirming the potential of these proteins as biomarkers for diagnosis, disease activity, and long-term disability outcomes. The study was funded by various research foundations in Sweden.

Source:

Journal Reference:

Åkesson, J., et al. (2023). Proteomics reveals biomarkers for diagnosis, disease activity, and long-term disability outcomes in multiple sclerosis. Nature Communications. doi.org/10.1038/s41467-023-42682-9.

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