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. 2024 Jul;11(4):e200259.
doi: 10.1212/NXI.0000000000200259. Epub 2024 May 29.

Single-Cell Transcriptomic Analyses of Brain Parenchyma in Patients With New-Onset Refractory Status Epilepticus (NORSE)

Aurélie Hanin  1 , Le Zhang  1 , Anita J Huttner  1 , Isabelle Plu  1 , Bertrand Mathon  1 , Franck Bielle  1 , Vincent Navarro  1 , Lawrence J Hirsch  1 , David A Hafler  1
Affiliations

Single-Cell Transcriptomic Analyses of Brain Parenchyma in Patients With New-Onset Refractory Status Epilepticus (NORSE)

Aurélie Hanin et al. Neurol Neuroimmunol Neuroinflamm. 2024 Jul.

Abstract

Background and objectives: New-onset refractory status epilepticus (NORSE) occurs in previously healthy children or adults, often followed by refractory epilepsy and poor outcomes. The mechanisms that transform a normal brain into an epileptic one capable of seizing for prolonged periods despite treatment remain unclear. Nonetheless, several pieces of evidence suggest that immune dysregulation could contribute to hyperexcitability and modulate NORSE sequelae.

Methods: We used single-nucleus RNA sequencing to delineate the composition and phenotypic states of the CNS of 4 patients with NORSE, to better understand the relationship between hyperexcitability and immune disturbances. We compared them with 4 patients with chronic temporal lobe epilepsy (TLE) and 2 controls with no known neurologic disorder.

Results: Patients with NORSE and TLE exhibited a significantly higher proportion of excitatory neurons compared with controls, with no discernible difference in inhibitory GABAergic neurons. When examining the ratio between excitatory neurons and GABAergic neurons for each patient individually, we observed a higher ratio in patients with acute NORSE or TLE compared with controls. Furthermore, a negative correlation was found between the ratio of excitatory to GABAergic neurons and the proportion of GABAergic neurons. The ratio between excitatory neurons and GABAergic neurons correlated with the proportion of resident or infiltrating macrophages, suggesting the influence of microglial reactivity on neuronal excitability. Both patients with NORSE and TLE exhibited increased expression of genes associated with microglia activation, phagocytic activity, and NLRP3 inflammasome activation. However, patients with NORSE had decreased expression of genes related to the downregulation of the inflammatory response, potentially explaining the severity of their presentation. Microglial activation in patients with NORSE also correlated with astrocyte reactivity, possibly leading to higher degrees of demyelination.

Discussion: Our study sheds light on the complex cellular dynamics in NORSE, revealing the potential roles of microglia, infiltrating macrophages, and astrocytes in hyperexcitability and demyelination, offering potential avenues for future research targeting the identified pathways.

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Conflict of interest statement

A. Hanin received postdoctoral grants from the Paratonnerre Association, the Servier Institute, the Philippe Foundation, the Swebilius Foundation, and the NORSE/FIRES Research Fund at Yale for NORSE-related research. L.J. Hirsch received support for investigator-initiated studies from The Daniel Raymond Wong Neurology Research Fund. L.J. Hirsch received funding from the NORSE/FIRES Research Fund at Yale. He received consultation fees for advising from Ceribell, Eisai, Marinus, Neurelis, Neuropace, Rafa Laboratories, and UCB; royalties from Wolters-Kluwer for authoring chapters for UpToDate-neurology and from Wiley for coauthoring the book Atlas of EEG in Critical Care, 1st and 2nd editions; honoraria for speaking from Neuropace, Natus, and UCB. Vincent Navarro reports personal fees from UCB Pharma, EISAI, GW Pharma, and Angellini, outside the submitted work. Other authors report no disclosures relevant to the manuscript. Go to Neurology.org/NN for full disclosures.

Figures

Figure 1
Figure 1. Single-Nucleus Isolation and Brain Cellular Population
(A) Description of the brain areas studied for each patient. The number of the patient is written below each female/male symbol. The same number was used for patients with several brain areas analyzed (e.g., NORSE#1). (B) UMAP (Uniform Manifold Approximation and Projection) shows the distribution of all brain cell nuclei within the frontal cortex (left), hippocampus (middle), and temporal cortex (right). (C) UMAP colored by gene expression of known lineage genes used to identify cell types. (D) UMAP shows the main cell types within the hippocampus. (E) Frequency distribution of the 8 main cell types within the frontal cortex, hippocampus, and temporal cortex for the different groups of patients.
Figure 2
Figure 2. Correlations Between the Different Cell Type Proportions
Heatmap showing correlations between the different cell type proportions. The heatmap colors correspond to correlations grading from −1 (negative correlation, blue), to no correlation (white), to 1 (positive correlation, red). * indicates p < 0.01 with Spearman analysis.
Figure 3
Figure 3. Microglia Reactivity in Patients With NORSE or Temporal Lobe Epilepsy
(A) UMAP for the nuclei belonging to the microglia cluster in the hippocampus. (B) Highlights of the number of genes overexpressed for control patients (CONT), patients with NORSE, or patients with temporal lobe epilepsy (TLE) compared with the other subgroups. (C-G) Violin plots for selected genes that were found differentially expressed among patients.
Figure 4
Figure 4. Astrocyte Reactivity in Patients With NORSE or Temporal Lobe Epilepsy
(A) Heatmap analysis revealing the differences in the gene expression between patients within the hippocampus. (B–D) Violin plots for selected genes that were found differentially expressed among patients, in the hippocampus (B–C), or frontal cortex (D).
Figure 5
Figure 5. Histopathology of the Hippocampus for a Panel of Patients Control, With TLE, or With NORSE
Iba-1 revealed gliosis for patients with TLE or NORSE. CD68 highlighted the infiltration of macrophages in the parenchyma of NORSE#1. CD163 revealed perivascular macrophages for TLE#2 and TLE#4. Scale bars: 50 µm.
Figure 6
Figure 6. T-Cell Infiltration in Patients With Cryptogenic Acute NORSE
(A) Individual proportion of T cells within the different brain areas. (B) UMAP for the hippocampus nuclei belonging to the T-cell cluster. (C) Pie charts showing the proportion of each T-cell cluster, for each patient, within the hippocampus. (D) UMAP colored by gene expression of known lineage genes used to identify the subtypes of T cells. (E) Heatmap analysis revealing the genes expressed by the nuclei from each subcluster within the hippocampus. (F) Plots highlighting the genes overexpressed by NORSE#1 compared with the other patients in the hippocampus (top), frontal cortex (middle), and temporal cortex (bottom). The genes with p < 0.01 and a fold-change above 1 are highlighted in red. The genes with p < 0.01 and a fold-change below −1 are highlighted in blue. The black dots correspond to genes with p > 0.01 and/or a fold-change from −1 to 1.
Figure 7
Figure 7. Schema Summarizing the Possible Mechanisms Involved in NORSE Onset and Consequences
See this image and copyright information in PMC

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