Molecular and spatial heterogeneity of microglia in Rasmussen encephalitis

Rasmussen encephalitis (RE) is a rare childhood neurological disease characterized by progressive unilateral loss of function, hemispheric atrophy and drug-resistant epilepsy. Affected brain tissue shows signs of infiltrating cytotoxic T-cells, microglial activation, and neuronal death, implicating an inflammatory disease process. Recent studies have identified molecular correlates of inflammation in RE, but cell-type-specific mechanisms remain unclear. We used single-nucleus RNA-sequencing (snRNA-seq) to assess gene expression across multiple cell types in brain tissue resected from two children with RE. We found transcriptionally distinct microglial populations enriched in RE compared to two age-matched individuals with unaffected brain tissue and two individuals with Type I focal cortical dysplasia (FCD). Specifically, microglia in RE tissues demonstrated upregulation of genes associated with cytokine signaling, interferon-mediated pathways, and T-cell activation. We extended these findings using spatial proteomic analysis of tissue from four surgical resections to examine expression profiles of microglia within their pathological context. Microglia that were spatially aggregated into nodules had increased expression of dynamic immune regulatory markers (PD-L1, CD14, CD11c), T-cell activation markers (CD40, CD80) and were physically located near distinct CD4+ and CD8+ lymphocyte populations. These findings help elucidate the complex immune microenvironment of RE. Overall design: We performed a comparitive analysis of single cell gene expression (10X Genomics 3' v3.1) between cortical tissue from patients with Rasmussen Encephalitis and from both non-diseased controls and a non-inflammatory epilepsy (Focal cortical dysplasia type I) samples. After QC and normalization, single cell gene expression datasets were integrated and cell types were determined using a combination of canonical markers and reference from Allen Barin Map [6] (Figure 1). We perfomed diffferential expression (DE) analysis via DESeq2 [28] and Gene Ontology (GO) Anotation enrichment analysis [13] of microglia across disease contitions (Figure 2). Louvain clustering was performed on the microglia and subsequent DE and GO annotation enrichment analysis were perfomed between the clusters (Figure 3).