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Autoimmune Encephalitis (AE) spans a group of non-infectious inflammatory conditions of the central nervous system due to an imbalanced immune response. Aiming to elucidate the pathophysiological mechanisms of AE, we applied an unsupervised proteomic approach to analyze the cerebrospinal fluid (CSF) protein profile of AE patients with autoantibodies against N -methyl- d -aspartate receptor (NMDAR) (n = 9), leucine-rich glioma-inactivated protein 1 (LGI1) (n = 9), or glutamate decarboxylase 65 (GAD65) (n = 8) compared to 9 patients with relapsing-remitting multiple sclerosis as inflammatory controls, and 10 patients with somatic symptom disorder as non-inflammatory controls. We found a dysregulation of the complement system, a disbalance between pro-inflammatory and anti-inflammatory proteins on the one hand, and dysregulation of proteins involved in synaptic transmission, synaptogenesis, brain connectivity, and neurodegeneration on the other hand to a different extent in all AE subtypes compared to non-inflammatory controls. Furthermore, elevated levels of several proteases and reduction in protease inhibitors could be detected in all AE subtypes compared to non-inflammatory controls. Moreover, the different AE subtypes showed distinct protein profiles compared to each other and inflammatory controls which may facilitate future identification of disease-specific biomarkers. Overall, CSF proteomics provides insights into the complex pathophysiological mechanisms of AE, including immune dysregulation, neuronal dysfunction, neurodegeneration, and altered protease function. • AE feature a dysregulation of CSF proteins involved in the cellular and humoral immune response. • Proteins associated with neuronal function and neurodegeneration are differentially regulated in AE compared to controls. • Higher levels of proteases and reduction in protease inhibitors could be detected in all AE subtypes compared to controls. • AE subtypes show distinct protein profiles, which could facilitate identification of potential disease-specific biomarkers. [ABSTRACT FROM AUTHOR]

Although CSF analysis routinely enables the diagnosis of neurological diseases, it is mainly used for the gross distinction between infectious, autoimmune inflammatory, and degenerative disorders of the CNS. To investigate, whether a multi-dimensional cellular blood and CSF characterization can support the diagnosis of clinically similar neurological diseases, we analysed 546 patients with autoimmune neuroinflammatory, degenerative, or vascular conditions in a cross-sectional retrospective study. By combining feature selection with dimensionality reduction and machine learning approaches we identified pan-disease parameters that were altered across all autoimmune neuroinflammatory CNS diseases and differentiated them from other neurological conditions and inter-autoimmunity classifiers that subdifferentiate variants of CNS-directed autoimmunity. Pan-disease as well as diseases-specific changes formed a continuum, reflecting clinical disease evolution. A validation cohort of 231 independent patients confirmed that combining multiple parameters into composite scores can assist the classification of neurological patients. Overall, we showed that the integrated analysis of blood and CSF parameters improves the differential diagnosis of neurological diseases, thereby facilitating early treatment decisions. [ABSTRACT FROM AUTHOR]