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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.

Recent evidence suggests that comorbidities between neuropsychiatric conditions and metabolic syndrome may precede and even exacerbate long-term side-effects of psychiatric medication, such as a higher risk of type 2 diabetes and cardiovascular disease, which result in increased mortality. In the present study we compare the expression of key metabolic proteins, including the insulin receptor (CD220), glucose transporter 1 (GLUT1) and fatty acid translocase (CD36), on peripheral blood mononuclear cell subtypes from patients across the neuropsychiatric spectrum, including schizophrenia, bipolar disorder, major depression and autism spectrum conditions (n = 25/condition), relative to typical controls (n = 100). This revealed alterations in the expression of these proteins that were specific to schizophrenia. Further characterization of metabolic alterations in an extended cohort of first-onset antipsychotic drug-naïve schizophrenia patients (n = 58) and controls (n = 63) revealed that the relationship between insulin receptor expression in monocytes and physiological insulin sensitivity was disrupted in schizophrenia and that altered expression of the insulin receptor was associated with whole genome polygenic risk scores for schizophrenia. Finally, longitudinal follow-up of the schizophrenia patients over the course of antipsychotic drug treatment revealed that peripheral metabolic markers predicted changes in psychopathology and the principal side effect of weight gain at clinically relevant time points. These findings suggest that peripheral blood cells can provide an accessible surrogate model for metabolic alterations in schizophrenia and have the potential to stratify subgroups of patients with different clinical outcomes or a greater risk of developing metabolic complications following antipsychotic therapy.