Neuroinflammatory disease signatures in SPG11-related hereditary spastic paraplegia patients

Biallelic loss of SPG11 function constitutes the most frequent cause of complicated autosomal recessive hereditary spastic paraplegia (HSP) with thin corpus callosum, resulting in progressive multisystem neurodegeneration. While the impact of neuroinflammation is an emerging and potentially treatable aspect in neurodegenerative diseases and leukodystrophies, the role of immune cells in SPG11-HSP patients is unknown. Here, we performed a comprehensive immunological characterization of SPG11-HSP, including examination of three human postmortem brain donations, immunophenotyping of patients' peripheral blood cells and patient-specific induced pluripotent stem cell-derived microglia-like cells (iMGL). We delineate a previously unknown role of innate immunity in SPG11-HSP. Neuropathological analysis of SPG11-HSP patient brain tissue revealed profound microgliosis in areas of neurodegeneration, downregulation of homeostatic microglial markers and cell-intrinsic accumulation of lipids and lipofuscin in IBA1+ cells. In a larger cohort of SPG11-HSP patients, the ratio of peripheral classical and intermediate monocytes was increased, along with increased serum levels of IL-6 that correlated with disease severity. Stimulation of patient-specific iMGLs with IFNγ led to increased phagocytic activity compared to control iMGL as well as increased upregulation and release of proinflammatory cytokines and chemokines, such as CXCL10. On a molecular basis, we identified increased STAT1 phosphorylation as mechanism connecting IFNγ-mediated immune hyperactivation and SPG11 loss of function. STAT1 expression was increased both in human postmortem brain tissue and in an Spg11-/- mouse model. Application of an STAT1 inhibitor decreased CXCL10 production in SPG11 iMGL and rescued their toxic effect on SPG11 neurons. Our data establish neuroinflammation as a novel disease mechanism in SPG11-HSP patients and constitute the first description of myeloid cell/ microglia activation in human SPG11-HSP. IFNγ/ STAT1-mediated neurotoxic effects of hyperreactive microglia upon SPG11 loss of function indicate that immunomodulation strategies may slow down disease progression.

Machine learning using multimodal and autonomic nervous system parameters predicts clinically apparent stroke-associated pneumonia in a development and testing study

BACKGROUND

Stroke-associated pneumonia (SAP) is a preventable determinant for poor outcome after stroke. Machine learning (ML) using large-scale clinical data warehouses may be able to predict SAP and identify patients for targeted interventions. The aim of this study was to develop a prediction model for identifying clinically apparent SAP using automated ML.

METHODS

The ML model used clinical and laboratory parameters along with heart rate (HR), heart rate variability (HRV), and blood pressure (BP) values obtained during the first 48 h after stroke unit admission. A logistic regression classifier was developed and internally validated with a nested-cross-validation (nCV) approach. For every shuffle, the model was first trained and validated with a fixed threshold for 0.9 sensitivity, then finally tested on the out-of-sample data and benchmarked against a widely validated clinical score (A2DS2).

RESULTS

We identified 2390 eligible patients admitted to two-stroke units at Charité between October 2020 and June 2023, of whom 1755 had all parameters available. SAP was diagnosed in 96/1755 (5.5%). Circadian profiles in HR, HRV, and BP metrics during the first 48 h after admission exhibited distinct differences between patients with SAP diagnosis vs. those without. CRP, mRS at admission, leukocyte count, high-frequency power in HRV, stroke severity at admission, sex, and diastolic BP were identified as the most informative ML features. We obtained an AUC of 0.91 (CI 0.88-0.95) for the ML model on the out-of-sample data in comparison to an AUC of 0.84 (CI 0.76-0.91) for the previously established A2DS2 score (p < 0.001). The ML model provided a sensitivity of 0.87 (CI 0.75-0.97) with a corresponding specificity of 0.82 (CI 0.78-0.85) which outperformed the A2DS2 score for multiple cutoffs.

CONCLUSIONS

Automated, data warehouse-based prediction of clinically apparent SAP in the stroke unit setting is feasible, benefits from the inclusion of vital signs, and could be useful for identifying high-risk patients or prophylactic pneumonia management in clinical routine.

The cellular microenvironment regulates CX3CR1 expression on CD8+ T cells and the maintenance of CX3CR1+ CD8+ T cells

Expression levels of the chemokine receptor CX3CR1 serve as high-resolution marker delineating functionally distinct antigen-experienced T-cell states. The factors that influence CX3CR1 expression in T cells are, however, incompletely understood. Here, we show that in vitro priming of naïve CD8+ T cells failed to robustly induce CX3CR1, which highlights the shortcomings of in vitro priming settings in recapitulating in vivo T-cell differentiation. Nevertheless, in vivo generated memory CD8+ T cells maintained CX3CR1 expression during culture. This allowed us to investigate whether T-cell receptor ligation, cell death, and CX3CL1 binding influence CX3CR1 expression. T-cell receptor stimulation led to downregulation of CX3CR1. Without stimulation, CX3CR1+ CD8+ T cells had a selective survival disadvantage, which was enhanced by factors released from necrotic but not apoptotic cells. Exposure to CX3CL1 did not rescue their survival and resulted in a dose-dependent loss of CX3CR1 surface expression. At physiological concentrations of CX3CL1, CX3CR1 surface expression was only minimally reduced, which did not hamper the interpretability of T-cell differentiation states delineated by CX3CR1. Our data further support the broad utility of CX3CR1 surface levels as T-cell differentiation marker and identify factors that influence CX3CR1 expression and the maintenance of CX3CR1 expressing CD8+ T cells.

Efficient and Easy Conversion of Human iPSCs into Functional Induced Microglia-like Cells

Current protocols converting human induced pluripotent stem cells (iPSCs) into induced microglia-like cells (iMGL) are either dependent on overexpression of transcription factors or require substantial experience in stem-cell technologies. Here, we developed an easy-to-use two-step protocol to convert iPSCs into functional iMGL via: (1) highly efficient differentiation of hematopoietic progenitor cells (HPCs) from iPSCs, and (2) optimized maturation of HPCs to iMGL. A sequential harvesting approach led to an increased HPC yield. The protocol implemented a freezing step, thus allowing HPC biobanking and flexible timing of differentiation into iMGL. Our iMGL responded adequately to the inflammatory stimuli LPS, and iMGL RNAseq analysis matched those of other frequently used protocols. Comparing three different coating modalities, we increased the iMGL yield by culturing on uncoated glass surfaces, thereby retaining differentiation efficiency and functional hallmarks of iMGL. In summary, we provide a high-quality, easy-to-use protocol, rendering generation and functional studies on iMGL an accessible lab resource.