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While posterior reversible encephalopathy syndrome (PRES) is often characterized by an inflammatory cerebrospinal-fluid (CSF) profile, knowledge of immune cell patterns in PRES is lacking. Thus, we retrospectively characterized CSF and peripheral blood (PB) from 15 PRES patients, which we analyzed by multidimensional flow cytometry (FC). Results were compared to 72 controls, as well as to 9 patients with progressive multifocal leukoencephalopathy (PML, as a relevant differential diagnosis) and 15 multiple sclerosis patients (MS, as a classical neuroinflammatory disorder), respectively. Total protein level in CSF from PRES patients was elevated compared to that in controls, but not to MS and PML. In-depth FC analysis revealed no differences for adaptive immune cells (B cells, plasma cells, CD4+, and CD8+ T cells) in PB or CSF of PRES compared to controls. In contrast, we observed alterations of the adaptive immune response in CSF of PML and MS compared to PRES, indicating that the adaptive immune response is not a driver of disease in PRES. Indeed, PRES was characterized by an innate immune response with CD14++/CD16+ (intermediate) monocytes elevated in PB and CSF, while CD14++/CD16− (classical) monocytes were decreased in PB from PRES patients as compared to controls. Levels of CD14++/CD16+ monocytes correlated with the duration of hospital stay as a surrogate marker for disease severity in PRES patients. Our findings argue for a role of innate rather than adaptive immunity in the pathophysiology of PRES. The observed shift in monocyte subsets might provide valuable diagnostic clues for the clinical management of these patients.

The central nervous system (CNS) is an immune-privileged compartment that is separated from the circulating blood and the peripheral organs by the blood&ndash, brain and the blood&ndash, cerebrospinal fluid (CSF) barriers. Transmigration of lymphocyte subsets across these barriers and their activation/differentiation within the periphery and intrathecal compartments in health and autoinflammatory CNS disease are complex. Mathematical models are warranted that qualitatively and quantitatively predict the distribution and differentiation stages of lymphocyte subsets in the blood and CSF. Here, we propose a probabilistic mathematical model that (i) correctly reproduces acquired data on location and differentiation states of distinct lymphocyte subsets under homeostatic and neuroinflammatory conditions, (ii) provides a quantitative assessment of differentiation and transmigration rates under these conditions, (iii) correctly predicts the qualitative behavior of immune-modulating therapies, (iv) and enables simulation-based prediction of distribution and differentiation stages of lymphocyte subsets in the case of limited access to biomaterial. Taken together, this model might reduce future measurements in the CSF compartment and allows for the assessment of the effectiveness of different immune-modulating therapies.

Objective: Utilize immune cell profiles in the cerebrospinal fluid (CSF) to advance the understanding and potentially support the diagnosis of inflammatory neuropathies. Methods: We analyzed CSF cell flow cytometry data of patients with definite Guillain-Barré syndrome (GBS, n = 26) and chronic inflammatory demyelinating polyneuropathy (CIDP, n = 32) based on established diagnostic criteria in comparison to controls with relapsing-remitting multiple sclerosis (RRMS, n = 49) and idiopathic intracranial hypertension (IIH, n = 63). Results: Flow cytometry revealed disease-specific changes of CSF cell composition with a significant increase of NKT cells and CD8+ T cells in CIDP, NK cells in GBS, and B cells and plasma cells in MS in comparison to IIH controls. Principal component analysis demonstrated distinct CSF immune cells pattern in inflammatory neuropathies vs. RRMS. Systematic receiver operator curve (ROC) analysis identified NKT cells as the best parameter to distinguish GBS from CIDP. Composite scores combing several of the CSF parameters differentiated inflammatory neuropathies from IIH and GBS from CIDP with high confidence. Applying a novel dimension reduction technique, we observed an intra-disease heterogeneity of inflammatory neuropathies. Conclusion: Inflammatory neuropathies display disease- and subtype-specific alterations of CSF cell composition. The increase of NKT cells and CD8+ T cells in CIDP and NK cells in GBS, suggests a central role of cytotoxic cell types in inflammatory neuropathies varying between acute and chronic subtypes. Composite scores constructed from multi-dimensional CSF parameters establish potential novel diagnostic tools. Intra-disease heterogeneity suggests distinct disease mechanisms in subgroups of inflammatory neuropathies.

Distinguishing neurosarcoidosis (NS) from multiple sclerosis (MS) remains challenging and available parameters lack discriminatory power. Comprehensive flow cytometry data of blood and CSF leukocytes of patients with NS (n = 24), MS (n = 49) and idiopathic intracranial hypertension (IIH, n = 52) were analyzed by machine learning algorithms. NS featured a specific immune cell pattern with increased activated CD4+ T cells in CSF and increased plasma cells in blood. Combining blood and CSF parameters improved the differentiation. We thereby identify and independently validate a multi-dimensional model of blood and CSF supporting the difficult differential diagnosis between NS and MS.