A large-scale proteomic analysis of cerebrospinal fluid samples has identified new protein markers for the diagnosis of multiple sclerosis (MS). The method, developed at the Max Planck Institute of Biochemistry, improves the ability to distinguish MS from similar inflammatory diseases of the central nervous system and also provides insights into the disease’s future course. In the future, this technology could also lead to the discovery of new biomarkers for other neurological disorders.
Nonspecific neurological symptoms such as numbness, visual disturbances, or severe fatigue often make it difficult to diagnose neurological disorders quickly. Despite modern imaging techniques, reliable molecular biomarkers are lacking for many diseases, which can lead to delayed or uncertain diagnoses.
A research team from the Technical University of Munich (TUM) and the Max Planck Institute (MPI) of Biochemistry has now identified new markers for multiple sclerosis using modern proteomics. The study analyzed cerebrospinal fluid samples from more than 5,000 patients with various neurological conditions - including strokes, brain tumors, infections, and autoimmune diseases - and systematically compared their protein profiles.
The study is based on a mass spectrometry technology developed at the MPI that enables the precise measurement of thousands of proteins in bodily fluids. This allows researchers to analyze the entire proteome of a sample without first having to select individual candidate proteins. This approach enables a significantly more comprehensive and faster search for disease-specific biomarkers.
For multiple sclerosis, the researchers identified a panel of 22 proteins that can distinguish MS from other inflammatory diseases of the central nervous system much more reliably than previously used cerebrospinal fluid parameters. This is particularly relevant for about 10 percent of MS patients who lack the classic diagnostic marker - oligoclonal antibody bands in the cerebrospinal fluid.
In addition to diagnostics, the analysis also provides insights into the later course of the disease. The study shows that the protein pattern in the cerebrospinal fluid is already linked to the long-term progression of the disease at the time of diagnosis. Certain protein signatures correlate with the risk of increasing disability as well as with the likelihood and speed of a transition from a relapsing-remitting to a progressive course of the disease.
The results suggest that important information about the future progression of the disease is already present in the cerebrospinal fluid proteome at an early stage. Such data could help tailor therapies more specifically to individual patients and enable earlier treatment decisions in the future.
Furthermore, the proteomic approach opens up new perspectives for neurological research as a whole. Since the method allows for the analysis of thousands of proteins in large patient cohorts, biomarkers for other diseases of the central nervous system - such as Alzheimer’s, Parkinson’s, or brain tumors - could also be discovered in the future.