Multiple sclerosis (MS) is the most common chronic inflammatory disease of the nervous system and a leading cause of disability in young adults. The incidence of MS is increasing worldwide, together with the socioeconomic impact of the disease. With the approval of several immunotherapies, but lacking effective biomarker for MS diagnosis and stratification of a disease with such highly variable course in patients, the decision of which treatment to use becomes increasingly complex. Furthermore, broad usage in early MS patients, in which these drugs are most efficient, is prevented by possible severe, even life-threating side effects and delayed diagnosis. Cerebrospinal fluid (CSF) is the body fluid closest to the pathology of multiple sclerosis, is relatively accessible and routinely obtained to support diagnosis of inflammatory and neurodegenerative diseases. However, the information obtained from CSF analysis has been limited and markers with high diagnostic sensitivity and specificity are not available for MS and for the majority of CNS diseases. Mass spectrometry-based proteomics is a powerful technology to discover new disease biomarker, but was so far not applicable to CSF samples. However, the group of Matthias Mann (Max Planck institute of Biochemistry, Munich) has largely advanced the proteomic analysis of CSF samples and established a rapid, robust, and highly reproducible robotic pipeline to specifically analyze CSF samples.Another rare, but severe autoimmune inflammatory process affecting the CNS, Neuromyelitis Optica (NMO), resembles multiple sclerosis but differs in distribution and histology of neuroinflammatory lesions and shows a more aggressive clinical course. NMO is also treated with immunosuppressive agents but no drug has been specifically approved for NMO yet.

The overarching aim of workpackage 1 is to provide a better understanding of proteomic changes associated with tissue destruction in chronic inflammatory diseases of the CNS, in particular MS and NMO, and pave the way for the development of diagnostic, prognostic and therapeutic biomarkers. To achieve this goal, an intradisciplinary team of outstanding scientists will perform proteomic analysis in CSF of a well-defined cohort of patients with MS and NMO with the aim to identify disease-specific proteomic changes and relate them to clinical and paraclinical outcome parameters.
The team of Prof. Bernhard Hemmer (Department of Neurology, University Hospital Rechts der Isar) and Prof. Mikael Simons (Institute of Neuronal Cell Biology, Technical University of Munich), renowned clinicians with particular expertise in the field of multiple sclerosis and other neuroinflammatory diseases, coordinate, assemble and provide patient cohorts from the existing Biobank. They further work on the standardization and availability of all phenotypic patient-derived data, assemble the genomic data of the patient cohorts and identify quality requirements of CSF samples for proteomic analysis. .

Sample processing and proteomic analysis are performed by experts in mass spectrometry-based proteomics from the group of Prof. Matthias Mann (Proteomics and Signal Transduction, Max Planck Institute of Biochemistry), who provide special expertise in sample preparation and proteomic analysis of CSF samples. The Team is further complemented by experienced bioinformaticians from the group of Prof. Fabian Theis (Institute of Computational Biology, Helmholtz Center Munich), who develop and apply new methods to implement an automated pipeline for data analysis of proteomic data from CSF samples.