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BackgroundVaccination has proven to be effective in preventing SARS-CoV-2 transmission and severe disease courses. However, immunocompromised patients have not been included in clinical trials and real-world clinical data point to an attenuated immune response to SARS-CoV-2 vaccines among patients with multiple sclerosis (MS) receiving immunomodulatory therapies.MethodsWe performed a retrospective study including 59 ocrelizumab (OCR)-treated patients with MS who received SARS-CoV-2 vaccination. Anti-SARS-CoV-2-antibody titres, routine blood parameters and peripheral immune cell profiles were measured prior to the first (baseline) and at a median of 4 weeks after the second vaccine dose (follow-up). Moreover, the SARS-CoV-2-specific T cell response and peripheral B cell subsets were analysed at follow-up. Finally, vaccination-related adverse events were assessed.ResultsAfter vaccination, we found anti-SARS-CoV-2(S) antibodies in 27.1% and a SARS-CoV-2-specific T cell response in 92.7% of MS cases. T cell-mediated interferon (IFN)-γ release was more pronounced in patients without anti-SARS-CoV-2(S) antibodies. Antibody titres positively correlated with peripheral B cell counts, time since last infusion and total IgM levels. They negatively correlated with the number of previous infusion cycles. Peripheral plasma cells were increased in antibody-positive patients. A positive correlation between T cell response and peripheral lymphocyte counts was observed. Moreover, IFN-γ release was negatively correlated with the time since the last infusion.ConclusionIn OCR-treated patients with MS, the humoral immune response to SARS-CoV-2 vaccination is attenuated while the T cell response is preserved. However, it is still unclear whether T or B cell-mediated immunity is required for effective clinical protection. Nonetheless, given the long-lasting clinical effects of OCR, monitoring of peripheral B cell counts could facilitate individualised treatment regimens and might be used to identify the optimal time to vaccinate.

Although cerebrospinal fluid (CSF) analysis routinely enables diagnosis of neurological diseases, it is mainly used for gross distinction between infectious, autoimmune inflammatory, and degenerative central nervous system (CNS) disorders. To investigate, whether a multi-dimensional cellular blood and CSF characterization can support the diagnosis of clinically similar neurological diseases, we analyzed 546 patients with autoimmune neuro-inflammatory, 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 altered across all autoimmune neuro-inflammatory CNS-diseases and differentiating them from other neurological conditions and inter-autoimmunity classifiers sub-differentiating 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 classification of neurological patients. Overall, we show that an integrated analysis of blood and CSF parameters improves differential diagnosis of neurological diseases, thereby facilitating early treatment decisions.

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Psychotic disorders are common and disabling mental conditions. The relative importance of immune-related mechanisms in psychotic disorders remains subject of debate. Here, we present a large-scale retrospective study of blood and cerebrospinal fluid (CSF) immune cell profiles of psychosis spectrum patients. We performed basic CSF analysis and multi-dimensional flow cytometry of CSF and blood cells from 59 patients with primary psychotic disorders (F20, F22, F23, and F25) in comparison to inflammatory (49 RRMS and 16 NMDARE patients) and non-inflammatory controls (52 IIH patients). We replicated the known expansion of monocytes in the blood of psychosis spectrum patients, that we identified to preferentially affect classical monocytes. In the CSF, we found a relative shift from lymphocytes to monocytes, increased protein levels, and evidence of blood–brain barrier disruption in psychosis. In fact, these CSF features confidently distinguished autoimmune encephalitis from psychosis despite similar (initial) clinical features. We then constructed machine learning models incorporating blood and CSF parameters and demonstrated their superior ability to differentiate psychosis from non-inflammatory controls compared to individual parameters. Multi-dimensional and multi-compartment immune cell signatures can thus support the diagnosis of psychosis spectrum disorders with the potential to accelerate diagnosis and initiation of therapy.