Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing

Abstract

Background: The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are different. This study aims to discover some specific and sensitive biomarkers to distinguish AE from IE at early stage to give specific treatments for good outcomes.

Results: We compared the host gene expression profiles and microbial diversities of cerebrospinal fluid (CSF) from 41 patients with IE and 18 patients with AE through meta-transcriptomic sequencing. Significant differences were found in host gene expression profiles and microbial diversities in CSF between patients with AE and patients with IE. The most significantly upregulated genes in patients with IE were enriched in pathways related with immune response such as neutrophil degranulation, antigen processing and presentation and adaptive immune system. In contrast, those upregulated genes in patients with AE were mainly involved in sensory organ development such as olfactory transduction, as well as synaptic transmission and signaling. Based on the differentially expressed genes, a classifier consisting of 5 host genes showed outstanding performance with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95.

Conclusions: This study provides a promising classifier and is the first to investigate transcriptomic signatures for differentiating AE from IE by using meta-transcriptomic next-generation sequencing technology.

Keywords: Autoimmune encephalitis; Cerebrospinal fluid; Infectious encephalitis; Next-generation sequencing (NGS); Transcriptomic signatures.

Fig. 1

Differential host responses in patients with IE compared to patients with AE. A The principal coordinate analysis plot showing the grouping of samples from the two groups based on global gene expression profiles. B The volcano plot of DEGs. The significant DEGs are highlighted in red (upregulated genes in IE) or green (down-regulated genes in IE). The unsignificant DEGs are marked in grey. The top 5 distinctly expressed genes are labeled. C The heatmap of differential expression of the top 15 significantly upregulated and downregulated genes across all the samples. The genes are ranked by P value. The color scale shows different values of log₂(TPM + 1) which indicates different gene expression levels. The red of the top group bar indicates samples from group IE and the cyan indicates group AE. D Gene functional enrichment analysis of DEGs. The heatmap indicates the top 20 representative enriched GO terms. E The heatmap showed the enriched GO terms associated with synapse. The color scale indicates the value of − log₁₀P

Fig. 2

The CSF microbial diversity analysis of patients with IE compared to patients with AE. A The principal coordinate analysis plot showing the grouping of samples based on the differences in beta-diversity of CSF microbiome. B The beta-diversity analysis of CSF microbiome, including Bray–Curtis distance, jaccard distance and jsd distance. The Wilcoxon rank-sum test was performed to assess the statistical significance. C The alpha-diversity analysis of CSF microbiome, including ACE, Shannon and Simpson index. The Wilcoxon rank-sum test was performed to assess the statistical significance. D The volcano plot of differentially abundant microbes between the two groups. The significantly differentially abundant microbes are highlighted in red (upregulated microbes in IE) or green (down-regulated microbes in IE). The unsignificant differentially abundant microbes are marked in grey. The top (ranked by adjusted p) differentially abundant microbes are labeled. E The heatmap of differential abundances of the top 15 (ranked by log₂FoldChange, adjusted p < 0.01) significantly upregulated and downregulated genera across all the samples

Fig. 3

Network analysis of the correlations of DEGs involved in neutrophil degranulation with CSF microbes and microbe-microbe interactions. A The interactions detected in patients with IE. B The interactions detected in AE cases. Each node represents one human gene or one microbial genus and the corresponding gene or microbe names are labeled. The yellow (P1) and magenta (P2) nodes indicate human genes involved in neutrophil degranulation and synaptic transmission and signaling respectively. The green, purple, blue and orange nodes indicate microbial genera belong to eukaryota, archaea, bacteria and viruses respectively. Red edges indicate negative correlations and green edges indicate positive correlations. The width of edge indicates interaction weight, and increases with the rise of weight. The size of node indicates the number of connections with other nodes, namely, the degree

Fig. 4

The receiver operating characteristic curve showing the performance of host transcriptomic signatures to distinguish AE from IE. A The ROC curve indicates the performance of 1-gene classifier. B The ROC curve indicates the performance of 5-gene classifier