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

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 o...

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Published inCell & bioscience Vol. 13; no. 1; pp. 111 - 15
Main Authors Fan, Siyuan, He, Xiangyan, Zhu, Zhongyi, Chen, Lu, Zou, Yijun, Chen, Zhonglin, Yu, Jialin, Chen, Weijun, Guan, Hongzhi, Ma, Jinmin
Format Journal Article
LanguageEnglish
Published England BioMed Central Ltd 19.06.2023
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Abstract 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. 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. 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.
AbstractList BackgroundThe 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.ResultsWe 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.ConclusionsThis 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.
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. 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. 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.
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.
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. 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. 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.
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: Infectious encephalitis, Autoimmune encephalitis, Transcriptomic signatures, Cerebrospinal fluid, Next-generation sequencing (NGS)
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.BACKGROUNDThe 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.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.RESULTSWe 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.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.CONCLUSIONSThis 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.
ArticleNumber 111
Audience Academic
Author Chen, Zhonglin
Zhu, Zhongyi
Zou, Yijun
Chen, Weijun
Guan, Hongzhi
Fan, Siyuan
He, Xiangyan
Chen, Lu
Yu, Jialin
Ma, Jinmin
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Issue 1
Keywords Transcriptomic signatures
Infectious encephalitis
Cerebrospinal fluid
Next-generation sequencing (NGS)
Autoimmune encephalitis
Language English
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Snippet The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are different. This...
Background The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are...
BackgroundThe early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them are...
Abstract Background The early accurate diagnoses for autoimmune encephalitis (AE) and infectious encephalitis (IE) are essential since the treatments for them...
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StartPage 111
SubjectTerms Antigen presentation
Antigen processing
Antigens
Autoimmune diseases
Autoimmune encephalitis
Biomarkers
Care and treatment
Cerebrospinal fluid
Comparative analysis
Degranulation
Encephalitis
Gene expression
Genes
Immune response
Infections
Infectious encephalitis
Leukocytes (neutrophilic)
Metagenomics
Neutrophils
Next-generation sequencing
Next-generation sequencing (NGS)
Pathogens
Patients
Proteins
Sense organs
Signal transduction
Synaptic transmission
Transcriptomic signatures
Transcriptomics
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Title Integrating host transcriptomic signatures for distinguishing autoimmune encephalitis in cerebrospinal fluid by metagenomic sequencing
URI https://www.ncbi.nlm.nih.gov/pubmed/37332019
https://www.proquest.com/docview/2838786254
https://www.proquest.com/docview/2827666407
https://pubmed.ncbi.nlm.nih.gov/PMC10278324
https://doaj.org/article/be4cc46b8f40402cb5160ab986e66169
Volume 13
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